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patriczhao pushed a commit to branch v1.x
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The following commit(s) were added to refs/heads/v1.x by this push:
new 36bd144 fix batchnorm (#18377) (#18470)
36bd144 is described below
commit 36bd144757586825fe78c7c2ec3db898daf1e19b
Author: Xinyu Chen <[email protected]>
AuthorDate: Wed Jun 3 13:46:42 2020 +0800
fix batchnorm (#18377) (#18470)
Update basic_layers.py
fix
fix
Update basic_layers.py
fix bug
Co-authored-by: Xingjian Shi <[email protected]>
---
python/mxnet/gluon/contrib/nn/basic_layers.py | 14 +++++++----
python/mxnet/gluon/nn/basic_layers.py | 36 +++++++++++++++------------
2 files changed, 29 insertions(+), 21 deletions(-)
diff --git a/python/mxnet/gluon/contrib/nn/basic_layers.py
b/python/mxnet/gluon/contrib/nn/basic_layers.py
index bc7c3ce..3c48a74 100644
--- a/python/mxnet/gluon/contrib/nn/basic_layers.py
+++ b/python/mxnet/gluon/contrib/nn/basic_layers.py
@@ -220,11 +220,15 @@ class SyncBatchNorm(BatchNorm):
center=True, scale=True, use_global_stats=False,
beta_initializer='zeros',
gamma_initializer='ones', running_mean_initializer='zeros',
running_variance_initializer='ones', **kwargs):
- fuse_relu = False
- super(SyncBatchNorm, self).__init__(1, momentum, epsilon, center,
scale, use_global_stats,
- fuse_relu, beta_initializer,
gamma_initializer,
- running_mean_initializer,
running_variance_initializer,
- in_channels, **kwargs)
+ super(SyncBatchNorm, self).__init__(
+ axis=1, momentum=momentum, epsilon=epsilon,
+ center=center, scale=scale,
+ use_global_stats=use_global_stats,
+ beta_initializer=beta_initializer,
+ gamma_initializer=gamma_initializer,
+ running_mean_initializer=running_mean_initializer,
+ running_variance_initializer=running_variance_initializer,
+ in_channels=in_channels, **kwargs)
num_devices = self._get_num_devices() if num_devices is None else
num_devices
self._kwargs = {'eps': epsilon, 'momentum': momentum,
'fix_gamma': not scale, 'use_global_stats':
use_global_stats,
diff --git a/python/mxnet/gluon/nn/basic_layers.py
b/python/mxnet/gluon/nn/basic_layers.py
index 70b0a71..72230fe 100644
--- a/python/mxnet/gluon/nn/basic_layers.py
+++ b/python/mxnet/gluon/nn/basic_layers.py
@@ -410,7 +410,6 @@ class BatchNorm(_BatchNorm):
If True, use global moving statistics instead of local batch-norm.
This will force
change batch-norm into a scale shift operator.
If False, use local batch-norm.
- fuse_relu: False
beta_initializer: str or `Initializer`, default 'zeros'
Initializer for the beta weight.
gamma_initializer: str or `Initializer`, default 'ones'
@@ -432,17 +431,20 @@ class BatchNorm(_BatchNorm):
- **out**: output tensor with the same shape as `data`.
"""
def __init__(self, axis=1, momentum=0.9, epsilon=1e-5, center=True,
scale=True,
- use_global_stats=False, fuse_relu=False,
+ use_global_stats=False,
beta_initializer='zeros', gamma_initializer='ones',
running_mean_initializer='zeros',
running_variance_initializer='ones',
in_channels=0, **kwargs):
- assert not fuse_relu, "Please use BatchNormReLU with Relu fusion"
super(BatchNorm, self).__init__(
- axis=1, momentum=0.9, epsilon=1e-5, center=True, scale=True,
- use_global_stats=False, fuse_relu=False,
- beta_initializer='zeros', gamma_initializer='ones',
- running_mean_initializer='zeros',
running_variance_initializer='ones',
- in_channels=0, **kwargs)
+ axis=axis, momentum=momentum, epsilon=epsilon, center=center,
+ scale=scale,
+ use_global_stats=use_global_stats, fuse_relu=False,
+ beta_initializer=beta_initializer,
+ gamma_initializer=gamma_initializer,
+ running_mean_initializer=running_mean_initializer,
+ running_variance_initializer=running_variance_initializer,
+ in_channels=in_channels, **kwargs)
+
class BatchNormReLU(_BatchNorm):
"""Batch normalization layer (Ioffe and Szegedy, 2014).
@@ -472,7 +474,6 @@ class BatchNormReLU(_BatchNorm):
If True, use global moving statistics instead of local batch-norm.
This will force
change batch-norm into a scale shift operator.
If False, use local batch-norm.
- fuse_relu: True
beta_initializer: str or `Initializer`, default 'zeros'
Initializer for the beta weight.
gamma_initializer: str or `Initializer`, default 'ones'
@@ -494,17 +495,20 @@ class BatchNormReLU(_BatchNorm):
- **out**: output tensor with the same shape as `data`.
"""
def __init__(self, axis=1, momentum=0.9, epsilon=1e-5, center=True,
scale=True,
- use_global_stats=False, fuse_relu=True,
+ use_global_stats=False,
beta_initializer='zeros', gamma_initializer='ones',
running_mean_initializer='zeros',
running_variance_initializer='ones',
in_channels=0, **kwargs):
- assert fuse_relu, "Please use BatchNorm w/o Relu fusion"
super(BatchNormReLU, self).__init__(
- axis=1, momentum=0.9, epsilon=1e-5, center=True, scale=True,
- use_global_stats=False, fuse_relu=True,
- beta_initializer='zeros', gamma_initializer='ones',
- running_mean_initializer='zeros',
running_variance_initializer='ones',
- in_channels=0, **kwargs)
+ axis=axis, momentum=momentum, epsilon=epsilon,
+ center=center, scale=scale,
+ use_global_stats=use_global_stats, fuse_relu=True,
+ beta_initializer=beta_initializer,
+ gamma_initializer=gamma_initializer,
+ running_mean_initializer=running_mean_initializer,
+ running_variance_initializer=running_variance_initializer,
+ in_channels=in_channels, **kwargs)
+
class Embedding(HybridBlock):
r"""Turns non-negative integers (indexes/tokens) into dense vectors
