trivial_model.py 1.55 KB
Newer Older
Haoyu Zhang's avatar
Haoyu Zhang committed
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
# 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.
# ==============================================================================
"""A trivial model for Keras."""

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


26
def trivial_model(num_classes, dtype='float32'):
Haoyu Zhang's avatar
Haoyu Zhang committed
27
28
29
  """Trivial model for ImageNet dataset."""

  input_shape = (224, 224, 3)
30
  img_input = layers.Input(shape=input_shape, dtype=dtype)
Haoyu Zhang's avatar
Haoyu Zhang committed
31
32
33

  x = layers.Lambda(lambda x: backend.reshape(x, [-1, 224 * 224 * 3]),
                    name='reshape')(img_input)
34
  x = layers.Dense(1, name='fc1')(x)
35
36
37
38
39
  x = layers.Dense(num_classes, name='fc1000')(x)
  # TODO(reedwm): Remove manual casts once mixed precision can be enabled with a
  # single line of code.
  x = backend.cast(x, 'float32')
  x = layers.Activation('softmax')(x)
Haoyu Zhang's avatar
Haoyu Zhang committed
40
41

  return models.Model(img_input, x, name='trivial')