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keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./keras/backend/jax/math.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./keras/layers/preprocessing/random_crop_test.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./keras/layers/core/dense.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./examples/keras_io/tensorflow/generative/vae.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./keras/utils/file_utils.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./keras/initializers/random_initializers.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./keras/backend/torch/image.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./keras/layers/preprocessing/rescaling.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./keras/trainers/__init__.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./keras/utils/io_utils.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./benchmarks/torch_ctl_benchmark/conv_model_benchmark.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./keras/utils/image_dataset_utils_test.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./examples/keras_io/structured_data/collaborative_filtering_movielens.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./keras/legacy/preprocessing/text.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./keras/backend/jax/rnn.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./examples/keras_io/vision/image_classification_with_vision_transformer.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./conftest.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./keras/backend/common/backend_utils.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./examples/keras_io/vision/pointnet_segmentation.py | -1 | python |
keras-team/keras | 18,815 | Added constant_values support to pad | jackd | 03f4a4fe3c0b2be47681e98275c11cd4bc786c8f | b4c3a0e163603855f03316b0b97f2c9c25e133eb | 2023-11-23 01:24:08+00:00 | 2023-11-24 18:00:28+00:00 | Added constant_values support to pad. Added `constant_values` kwarg to `ops.pad`. This argument is ignored if `mode != 'constant'`, which is different to `numpy` which raises. | ./keras/backend/common/variables_test.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/ops/numpy_test.py | 1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/ops/numpy.py | 1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/backend/tensorflow/numpy.py | 1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/backend/numpy/numpy.py | 1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/backend/jax/numpy.py | 1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/backend/torch/numpy.py | 1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/utils/tracking.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/layers/reshaping/up_sampling3d.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/datasets/boston_housing.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/utils/dtype_utils_test.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/regularizers/regularizers.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/optimizers/adagrad.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./examples/keras_io/tensorflow/vision/grad_cam.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/callbacks/learning_rate_scheduler.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/applications/imagenet_utils.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/layers/convolutional/depthwise_conv_test.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/backend/common/dtypes_test.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./examples/demo_custom_torch_workflow.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/callbacks/csv_logger_test.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/legacy/__init__.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/layers/attention/__init__.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/optimizers/schedules/learning_rate_schedule.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./examples/keras_io/tensorflow/keras_recipes/trainer_pattern.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/utils/dataset_utils.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/layers/merging/minimum.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./benchmarks/layer_benchmark/attention_benchmark.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/layers/regularization/gaussian_dropout_test.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/trainers/data_adapters/tf_dataset_adapter.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/applications/mobilenet.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./examples/keras_io/structured_data/collaborative_filtering_movielens.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/losses/loss_test.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/optimizers/adamw.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/backend/common/global_state_test.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/legacy/saving/__init__.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/trainers/epoch_iterator_test.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/layers/attention/grouped_query_attention_test.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/layers/input_spec.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/layers/merging/subtract.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/layers/convolutional/separable_conv1d.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/export/__init__.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/ops/__init__.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./examples/keras_io/vision/gradient_centralization.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/utils/argument_validation.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/layers/convolutional/conv2d_transpose.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/layers/merging/add.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/layers/merging/concatenate.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./integration_tests/torch_workflow_test.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/initializers/__init__.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./examples/keras_io/generative/text_generation_with_miniature_gpt.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/legacy/saving/serialization.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/optimizers/ftrl_test.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/optimizers/adafactor_test.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/layers/preprocessing/integer_lookup.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/legacy/preprocessing/text.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/metrics/metric_test.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./examples/keras_io/tensorflow/rl/actor_critic_cartpole.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./examples/keras_io/nlp/lstm_seq2seq.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/layers/core/lambda_layer.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/layers/preprocessing/random_contrast_test.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./examples/keras_io/generative/pixelcnn.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./examples/keras_io/tensorflow/vision/perceiver_image_classification.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/trainers/data_adapters/py_dataset_adapter_test.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/utils/image_dataset_utils_test.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/layers/rnn/gru.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./guides/making_new_layers_and_models_via_subclassing.py | -1 | python |
keras-team/keras | 18,813 | added dtype arg to cumsum/cumprod, fixes inconsistency bug | jackd | 46853c8b611c15be60c98e31edf47b0e1769f365 | f0f29d14a868fa86e124b091d42bb37995a31dd5 | 2023-11-23 00:06:28+00:00 | 2023-11-23 04:35:36+00:00 | added dtype arg to cumsum/cumprod, fixes inconsistency bug. Addresses #18730 . I've adopted the jax convention of defaulting dtype to the original in the case of ints, rather than integer type promotion as is the numpy/tensorflow/torch approach. | ./keras/callbacks/terminate_on_nan.py | -1 | python |
keras-team/keras | 18,806 | Support channels_first in rnn layers | haifeng-jin | 443b0db9d63ff226040aeb5b66c2e7bd71381f71 | a6d93e9385191cbcce357bb0e7e8573cd56c17c3 | 2023-11-20 23:35:42+00:00 | 2023-11-21 04:08:16+00:00 | Support channels_first in rnn layers. | ./keras/layers/rnn/conv_lstm3d_test.py | 1 | python |
keras-team/keras | 18,806 | Support channels_first in rnn layers | haifeng-jin | 443b0db9d63ff226040aeb5b66c2e7bd71381f71 | a6d93e9385191cbcce357bb0e7e8573cd56c17c3 | 2023-11-20 23:35:42+00:00 | 2023-11-21 04:08:16+00:00 | Support channels_first in rnn layers. | ./keras/layers/rnn/time_distributed_test.py | 1 | python |
keras-team/keras | 18,806 | Support channels_first in rnn layers | haifeng-jin | 443b0db9d63ff226040aeb5b66c2e7bd71381f71 | a6d93e9385191cbcce357bb0e7e8573cd56c17c3 | 2023-11-20 23:35:42+00:00 | 2023-11-21 04:08:16+00:00 | Support channels_first in rnn layers. | ./keras/layers/rnn/conv_lstm_test.py | 1 | python |
keras-team/keras | 18,806 | Support channels_first in rnn layers | haifeng-jin | 443b0db9d63ff226040aeb5b66c2e7bd71381f71 | a6d93e9385191cbcce357bb0e7e8573cd56c17c3 | 2023-11-20 23:35:42+00:00 | 2023-11-21 04:08:16+00:00 | Support channels_first in rnn layers. | ./keras/layers/rnn/conv_lstm1d_test.py | 1 | python |
keras-team/keras | 18,806 | Support channels_first in rnn layers | haifeng-jin | 443b0db9d63ff226040aeb5b66c2e7bd71381f71 | a6d93e9385191cbcce357bb0e7e8573cd56c17c3 | 2023-11-20 23:35:42+00:00 | 2023-11-21 04:08:16+00:00 | Support channels_first in rnn layers. | ./keras/layers/rnn/conv_lstm2d_test.py | 1 | python |
keras-team/keras | 18,806 | Support channels_first in rnn layers | haifeng-jin | 443b0db9d63ff226040aeb5b66c2e7bd71381f71 | a6d93e9385191cbcce357bb0e7e8573cd56c17c3 | 2023-11-20 23:35:42+00:00 | 2023-11-21 04:08:16+00:00 | Support channels_first in rnn layers. | ./examples/keras_io/timeseries/timeseries_anomaly_detection.py | -1 | python |
keras-team/keras | 18,806 | Support channels_first in rnn layers | haifeng-jin | 443b0db9d63ff226040aeb5b66c2e7bd71381f71 | a6d93e9385191cbcce357bb0e7e8573cd56c17c3 | 2023-11-20 23:35:42+00:00 | 2023-11-21 04:08:16+00:00 | Support channels_first in rnn layers. | ./examples/keras_io/structured_data/tabtransformer.py | -1 | python |
keras-team/keras | 18,806 | Support channels_first in rnn layers | haifeng-jin | 443b0db9d63ff226040aeb5b66c2e7bd71381f71 | a6d93e9385191cbcce357bb0e7e8573cd56c17c3 | 2023-11-20 23:35:42+00:00 | 2023-11-21 04:08:16+00:00 | Support channels_first in rnn layers. | ./keras/metrics/accuracy_metrics.py | -1 | python |
keras-team/keras | 18,806 | Support channels_first in rnn layers | haifeng-jin | 443b0db9d63ff226040aeb5b66c2e7bd71381f71 | a6d93e9385191cbcce357bb0e7e8573cd56c17c3 | 2023-11-20 23:35:42+00:00 | 2023-11-21 04:08:16+00:00 | Support channels_first in rnn layers. | ./keras/layers/pooling/global_average_pooling2d.py | -1 | python |
keras-team/keras | 18,806 | Support channels_first in rnn layers | haifeng-jin | 443b0db9d63ff226040aeb5b66c2e7bd71381f71 | a6d93e9385191cbcce357bb0e7e8573cd56c17c3 | 2023-11-20 23:35:42+00:00 | 2023-11-21 04:08:16+00:00 | Support channels_first in rnn layers. | ./keras/layers/rnn/__init__.py | -1 | python |
keras-team/keras | 18,806 | Support channels_first in rnn layers | haifeng-jin | 443b0db9d63ff226040aeb5b66c2e7bd71381f71 | a6d93e9385191cbcce357bb0e7e8573cd56c17c3 | 2023-11-20 23:35:42+00:00 | 2023-11-21 04:08:16+00:00 | Support channels_first in rnn layers. | ./keras/trainers/data_adapters/generator_data_adapter.py | -1 | python |
keras-team/keras | 18,806 | Support channels_first in rnn layers | haifeng-jin | 443b0db9d63ff226040aeb5b66c2e7bd71381f71 | a6d93e9385191cbcce357bb0e7e8573cd56c17c3 | 2023-11-20 23:35:42+00:00 | 2023-11-21 04:08:16+00:00 | Support channels_first in rnn layers. | ./keras/ops/core.py | -1 | python |
keras-team/keras | 18,806 | Support channels_first in rnn layers | haifeng-jin | 443b0db9d63ff226040aeb5b66c2e7bd71381f71 | a6d93e9385191cbcce357bb0e7e8573cd56c17c3 | 2023-11-20 23:35:42+00:00 | 2023-11-21 04:08:16+00:00 | Support channels_first in rnn layers. | ./keras/backend/common/keras_tensor_test.py | -1 | python |
keras-team/keras | 18,806 | Support channels_first in rnn layers | haifeng-jin | 443b0db9d63ff226040aeb5b66c2e7bd71381f71 | a6d93e9385191cbcce357bb0e7e8573cd56c17c3 | 2023-11-20 23:35:42+00:00 | 2023-11-21 04:08:16+00:00 | Support channels_first in rnn layers. | ./keras/layers/reshaping/permute_test.py | -1 | python |