Spaces:
Running
Running
# Copyright 2018 The TensorFlow Authors. All Rights Reserved. | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
# ============================================================================== | |
"""Test utilities for image classification tasks.""" | |
from __future__ import absolute_import | |
from __future__ import division | |
from __future__ import print_function | |
from tensorflow.python.keras import backend | |
from tensorflow.python.keras import layers | |
from tensorflow.python.keras import models | |
def trivial_model(num_classes): | |
"""Trivial model for ImageNet dataset.""" | |
input_shape = (224, 224, 3) | |
img_input = layers.Input(shape=input_shape) | |
x = layers.Lambda(lambda x: backend.reshape(x, [-1, 224 * 224 * 3]), | |
name='reshape')(img_input) | |
x = layers.Dense(1, name='fc1')(x) | |
x = layers.Dense(num_classes, name='fc1000')(x) | |
x = layers.Activation('softmax', dtype='float32')(x) | |
return models.Model(img_input, x, name='trivial') | |