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14f11c9e
编写于
6月 23, 2021
作者:
A
A. Unique TensorFlower
提交者:
TensorFlower Gardener
6月 23, 2021
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Mention functional API in the migration docstrings of core.py.
PiperOrigin-RevId: 381059294
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keras/legacy_tf_layers/core.py
keras/legacy_tf_layers/core.py
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keras/legacy_tf_layers/core.py
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14f11c9e
...
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@@ -90,7 +90,7 @@ class Dense(keras_layers.Dense, base.Layer):
Please refer to [tf.layers section of the migration guide]
(https://www.tensorflow.org/guide/migrate#models_based_on_tflayers)
for more details on migrating a TF1 model to Keras. In TF2 the corresponding
to migrate a TensorFlow v1 model to Keras. The corresponding TensorFlow v2
layer is `tf.keras.layers.Dense`.
...
...
@@ -206,7 +206,7 @@ def dense(
Please refer to [tf.layers section of the migration guide]
(https://www.tensorflow.org/guide/migrate#models_based_on_tflayers)
for more details on migrating a TF1 model to Keras. In TF2 the corresponding
to migrate a TensorFlow v1 model to Keras. The corresponding TensorFlow v2
layer is `tf.keras.layers.Dense`.
...
...
@@ -222,8 +222,13 @@ def dense(
After:
To migrate code using TF1 functional layers use the [Keras Functional API]
(https://www.tensorflow.org/guide/keras/functional):
```python
x = tf.keras.Input((28,))
y = tf.keras.layers.Dense(units=3)(x)
model = tf.keras.Model(x, y)
```
@end_compatibility
...
...
@@ -278,7 +283,7 @@ class Dropout(keras_layers.Dropout, base.Layer):
Please refer to [tf.layers section of the migration guide]
(https://www.tensorflow.org/guide/migrate#models_based_on_tflayers)
for more details on migrating a TF1 model to Keras. In TF2 the corresponding
to migrate a TensorFlow v1 model to Keras. The corresponding TensorFlow v2
layer is `tf.keras.layers.Dropout`.
...
...
@@ -359,7 +364,7 @@ def dropout(inputs,
Please refer to [tf.layers section of the migration guide]
(https://www.tensorflow.org/guide/migrate#models_based_on_tflayers)
for more details on migrating a TF1 model to Keras. In TF2 the corresponding
to migrate a TensorFlow v1 model to Keras. The corresponding TensorFlow v2
layer is `tf.keras.layers.Dropout`.
...
...
@@ -375,8 +380,13 @@ def dropout(inputs,
After:
To migrate code using TF1 functional layers use the [Keras Functional API]
(https://www.tensorflow.org/guide/keras/functional):
```python
x = tf.keras.Input((28, 28, 1))
y = tf.keras.layers.Dropout()(x)
model = tf.keras.Model(x, y)
```
@end_compatibility
"""
...
...
@@ -416,7 +426,7 @@ class Flatten(keras_layers.Flatten, base.Layer):
Please refer to [tf.layers section of the migration guide]
(https://www.tensorflow.org/guide/migrate#models_based_on_tflayers)
for more details on migrating a TF1 model to Keras. In TF2 the corresponding
to migrate a TensorFlow v1 model to Keras. The corresponding TensorFlow v2
layer is `tf.keras.layers.Flatten`.
...
...
@@ -474,7 +484,7 @@ def flatten(inputs, name=None, data_format='channels_last'):
Please refer to [tf.layers section of the migration guide]
(https://www.tensorflow.org/guide/migrate#models_based_on_tflayers)
for more details on migrating a TF1 model to Keras. In TF2 the corresponding
to migrate a TensorFlow v1 model to Keras. The corresponding TensorFlow v2
layer is `tf.keras.layers.Flatten`.
...
...
@@ -490,8 +500,13 @@ def flatten(inputs, name=None, data_format='channels_last'):
After:
To migrate code using TF1 functional layers use the [Keras Functional API]
(https://www.tensorflow.org/guide/keras/functional):
```python
x = tf.keras.Input((28, 28, 1))
y = tf.keras.layers.Flatten()(x)
model = tf.keras.Model(x, y)
```
@end_compatibility
"""
...
...
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