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keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/models/__init__.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/metrics/__init__.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/version.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/backend/common/backend_utils_test.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/metrics/metric.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/utils/dataset_utils_test.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/activations/__init__.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/applications/resnet.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./integration_tests/basic_full_flow.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/legacy/saving/json_utils_test.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./guides/distributed_training_with_tensorflow.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/legacy/__init__.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/utils/io_utils.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/applications/efficientnet_v2.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/callbacks/learning_rate_scheduler.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/layers/pooling/global_max_pooling3d.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/constraints/constraints_test.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/trainers/data_adapters/py_dataset_adapter_test.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/saving/serialization_lib_test.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/backend/torch/optimizers/torch_adadelta.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/backend/tensorflow/distribute_test.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./examples/keras_io/tensorflow/nlp/text_classification_from_scratch.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/callbacks/callback.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./examples/keras_io/tensorflow/generative/ddim.py | -1 | python |
keras-team/keras | 18,838 | Some improvements in numpy api | james77777778 | df3394d0ee2c33268390811ee039448788150fcd | 5b9f1b70dca1ac3b7a307f0ddbbe5df816dfe5b7 | 2023-11-28 03:40:15+00:00 | 2023-11-29 01:58:13+00:00 | Some improvements in numpy api. This PR includes the following:
- Added `convert_to_tensor` in JAX's (inverse) trigonometric functions to ensure that x contains `dtype` attribute, as it is needed for dtype inference
- Applied `backend.result_type` to `var`
- Promoted dtype to int32 in `clip` instead of int64 when the incoming dtype is bool
- Fixed dtype conversion of `trace` as mentioned in https://github.com/keras-team/keras/pull/18831#discussion_r1406344825
<details>
- [x] abs
- [x] absolute
- [x] add
- [x] all
- [x] amax
- [x] amin
- [x] append
- [x] arange
- [x] arccos
- [x] arccosh
- [x] arcsin
- [x] arcsinh
- [x] arctan
- [x] arctan2
- [x] arctanh
- [x] argmax
- [x] argmin
- [x] argsort
- [x] array
- [x] average
- [x] bincount
- [x] broadcast_to
- [x] ceil
- [x] clip
- [x] concatenate
- [ ] conj (Keras does not directly support complex data)
- [ ] conjugate (Keras does not directly support complex data)
- [x] copy
- [x] cos
- [x] cosh
- [x] count_nonzero
- [x] cross
- [x] cumprod
- [x] cumsum
- [x] diag
- [x] diagonal
- [x] diff
- [x] digitize
- [x] divide
- [x] dot
- [x] einsum
- [x] empty
- [x] equal
- [x] exp
- [x] expand_dims
- [x] expm1
- [x] eye
- [x] flip
- [x] floor
- [x] full
- [x] full_like
- [x] greater
- [x] greater_equal
- [x] hstack
- [x] identity
- [ ] imag (Keras does not directly support complex data)
- [ ] interp (Keras lacks this op)
- [x] isclose
- [x] isfinite
- [x] isinf
- [x] isnan
- [x] less
- [x] less_equal
- [x] linspace
- [x] log
- [x] log10
- [x] log1p
- [x] log2
- [x] logaddexp
- [x] logical_and
- [x] logical_not
- [x] logical_or
- [x] logspace
- [x] matmul
- [x] max
- [x] maximum
- [x] mean
- [x] median
- [x] meshgrid
- [ ] mgrid (Keras lacks this op)
- [x] min
- [x] minimum
- [x] mod
- [x] moveaxis
- [x] multiply
- [x] nan_to_num
- [ ] ndim
- [x] nonzero
- [x] not_equal
- [x] ones
- [x] ones_like
- [x] outer
- [x] pad
- [ ] percentile (Keras lacks this op)
- [x] power
- [x] prod
- [x] quantile
- [x] ravel
- [ ] real (Keras does not directly support complex data)
- [ ] reciprocal (Keras lacks this op)
- [x] repeat
- [x] reshape
- [x] roll
- [x] round
- [x] sign
- [x] sin
- [x] sinh
- [ ] size
- [x] sort
- [x] split
- [x] sqrt
- [x] square
- [x] squeeze
- [x] stack
- [x] std
- [x] subtract
- [x] sum
- [x] swapaxes
- [x] take
- [x] take_along_axis
- [x] tan
- [x] tanh
- [x] tensordot
- [x] tile
- [x] trace
- [x] transpose
- [x] tri
- [x] tril
- [x] triu
- [x] true_divide
- [x] var
- [x] vdot
- [x] vstack
- [x] where
- [x] zeros
- [x] zeros_like
</details> | ./keras/layers/merging/maximum.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/backend/jax/__init__.py | 1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/backend/tensorflow/core.py | 1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/backend/torch/core.py | 1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/backend/jax/core.py | 1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/backend/tensorflow/__init__.py | 1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/backend/torch/__init__.py | 1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/preprocessing/normalization_test.py | 1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./examples/keras_io/tensorflow/timeseries/timeseries_traffic_forecasting.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/utils/code_stats_test.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/export/export_lib.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/reshaping/up_sampling2d_test.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/legacy/saving/json_utils.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/random/seed_generator.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/trainers/data_adapters/array_data_adapter_test.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./guides/custom_train_step_in_torch.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/models/__init__.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/backend/tensorflow/rnn.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/saving/saving_api.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./examples/keras_io/tensorflow/vision/perceiver_image_classification.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/pooling/global_max_pooling3d.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./guides/distributed_training_with_torch.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/callbacks/terminate_on_nan_test.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/preprocessing/hashed_crossing_test.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/legacy/backend.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/trainers/data_adapters/data_adapter.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/normalization/batch_normalization.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/preprocessing/discretization_test.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/attention/multi_head_attention.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./examples/keras_io/vision/object_detection_using_vision_transformer.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/utils/text_dataset_utils_test.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/utils/rng_utils.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/backend/config.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/optimizers/optimizer.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/utils/timeseries_dataset_utils_test.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/optimizers/adafactor_test.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/reshaping/zero_padding2d_test.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./examples/keras_io/tensorflow/audio/transformer_asr.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./examples/demo_subclass.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./benchmarks/layer_benchmark/conv_benchmark.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/optimizers/sgd.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/trainers/data_adapters/generator_data_adapter.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/pooling/__init__.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/pooling/global_average_pooling1d.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./benchmarks/layer_benchmark/base_benchmark.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/ops/image.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/trainers/__init__.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/utils/torch_utils.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/applications/mobilenet.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/optimizers/base_optimizer.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/datasets/reuters.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/convolutional/conv2d.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./examples/keras_io/tensorflow/vision/reptile.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/backend/numpy/layer.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/utils/audio_dataset_utils.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/normalization/unit_normalization.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./examples/keras_io/nlp/neural_machine_translation_with_transformer.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/optimizers/adadelta.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/core/__init__.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/callbacks/learning_rate_scheduler.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/activations/elu_test.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/reshaping/zero_padding1d.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/backend/torch/optimizers/torch_adamax.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/callbacks/remote_monitor_test.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/backend/jax/distribution_lib.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./README.md | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/regularizers/regularizers_test.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/reshaping/zero_padding3d_test.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/backend/torch/optimizers/torch_optimizer.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./examples/keras_io/tensorflow/vision/deit.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/metrics/metrics_utils.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/regularization/activity_regularization.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/regularization/dropout_test.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/convolutional/conv2d_transpose.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/utils/code_stats.py | -1 | python |
keras-team/keras | 18,837 | Add keras.backend.device() API for device scope | qlzh727 | 06d31d9e06d74dcf932d830bbdf1e4bf1447bf87 | 1ebe1d052e27166ebcd4fe8ffaa6fb7637c97d8f | 2023-11-27 23:51:38+00:00 | 2023-11-29 19:33:56+00:00 | Add keras.backend.device() API for device scope. | ./keras/layers/core/einsum_dense_test.py | -1 | python |