diff options
| author |  James Qin <jamesqin@google.com> | 2018-06-14 02:02:26 -0700 |
|---|---|---|
| committer |  TensorFlower Gardener <gardener@tensorflow.org> | 2018-06-14 02:04:54 -0700 |
| commit | 0b8c5806f4f1d3a47b30bf203b3e456f036b0adc (patch) | |
| tree | 3bb6da10c88306134dda7f530e470200e56b7276 /tensorflow/python/layers | |
| parent | c570211c5cd972a278366d3d3fd65ee8f99836aa (diff) | |
Remove hardcoded dtype in tf.layers.xxx() function call to make them compatible with mixed precision training apis.
tf.layers.foolayer(inputs) creates a tf.layer.FooLayer(dtype=inputs.dtype) and immediately invokes __call__() on the input.
The dtype in the Foolayer() constructor isn't needed. Plus it stands in the way for global mixed precision dtype we plan to add in the future.
PiperOrigin-RevId: 200524027
Diffstat (limited to 'tensorflow/python/layers')
| -rw-r--r-- | tensorflow/python/layers/convolutional.py | 5 | ||||
| -rw-r--r-- | tensorflow/python/layers/core.py | 1 | ||||
| -rw-r--r-- | tensorflow/python/layers/normalization.py | 1 |
3 files changed, 0 insertions, 7 deletions
diff --git a/tensorflow/python/layers/convolutional.py b/tensorflow/python/layers/convolutional.py index 267d78dbcb..36cef3855e 100644 --- a/tensorflow/python/layers/convolutional.py +++ b/tensorflow/python/layers/convolutional.py @@ -217,7 +217,6 @@ def conv1d(inputs, bias_constraint=bias_constraint, trainable=trainable, name=name, - dtype=inputs.dtype.base_dtype, _reuse=reuse, _scope=name) return layer.apply(inputs) @@ -421,7 +420,6 @@ def conv2d(inputs, bias_constraint=bias_constraint, trainable=trainable, name=name, - dtype=inputs.dtype.base_dtype, _reuse=reuse, _scope=name) return layer.apply(inputs) @@ -627,7 +625,6 @@ def conv3d(inputs, bias_constraint=bias_constraint, trainable=trainable, name=name, - dtype=inputs.dtype.base_dtype, _reuse=reuse, _scope=name) return layer.apply(inputs) @@ -1266,7 +1263,6 @@ def conv2d_transpose(inputs, bias_constraint=bias_constraint, trainable=trainable, name=name, - dtype=inputs.dtype.base_dtype, _reuse=reuse, _scope=name) return layer.apply(inputs) @@ -1438,7 +1434,6 @@ def conv3d_transpose(inputs, bias_constraint=bias_constraint, trainable=trainable, name=name, - dtype=inputs.dtype.base_dtype, _reuse=reuse, _scope=name) return layer.apply(inputs) diff --git a/tensorflow/python/layers/core.py b/tensorflow/python/layers/core.py index abbacac442..aadff231da 100644 --- a/tensorflow/python/layers/core.py +++ b/tensorflow/python/layers/core.py @@ -184,7 +184,6 @@ def dense( bias_constraint=bias_constraint, trainable=trainable, name=name, - dtype=inputs.dtype.base_dtype, _scope=name, _reuse=reuse) return layer.apply(inputs) diff --git a/tensorflow/python/layers/normalization.py b/tensorflow/python/layers/normalization.py index d082e312e9..ece6667981 100644 --- a/tensorflow/python/layers/normalization.py +++ b/tensorflow/python/layers/normalization.py @@ -308,7 +308,6 @@ def batch_normalization(inputs, virtual_batch_size=virtual_batch_size, adjustment=adjustment, name=name, - dtype=inputs.dtype.base_dtype, _reuse=reuse, _scope=name) return layer.apply(inputs, training=training) |