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Support NHWC in Pool2D, test=develop (#24240)

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* support NHWC in Pool2D, test=develop

* add unittest, test=develop

* fix unittest, test=develop

* fix typo, test=develop

* follow comments, test=develop

* refine comments, test=develop
v1.8
Leo Chen 5 years ago committed by GitHub
parent 37ae661ca1
commit 9fd1aad6e7
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GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 94 additions and 6 deletions
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26
python/paddle/fluid/dygraph/nn.py
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@ -771,14 +771,19 @@ class Pool2D(layers.Layer):
ceil_mode (bool, optional): Whether to use the ceil function to calculate output height and width.
False is the default. If it is set to False, the floor function will be used. Default: False.
exclusive (bool, optional): Whether to exclude padding points in average pooling mode. Default: True.
data_format (string): The data format of the input and output data. An optional string from: `"NCHW"`, `"NHWC"`.
The default is `"NCHW"`. When it is `"NCHW"`, the data is stored in the order of:
``[batch_size, input_channels, input_height, input_width]``. When it is `"NHWC"`, the data is
stored in the order of: ``[batch_size, input_height, input_width, input_channels]``
Returns:
None
Raises:
ValueError: If 'pool_type' is not "max" nor "avg"
ValueError: If 'global_pooling' is False and 'pool_size' is -1
ValueError: If 'use_cudnn' is not a bool value.
ValueError: If ``pool_type`` is not "max" nor "avg".
ValueError: If ``global_pooling`` is False and ``pool_size`` is -1.
ValueError: If ``use_cudnn`` is not a bool value.
ValueError: If ``data_format`` is not "NCHW" nor "NHWC".
Examples:
@ -806,7 +811,10 @@ class Pool2D(layers.Layer):
global_pooling=False,
use_cudnn=True,
ceil_mode=False,
exclusive=True):
exclusive=True,
data_format="NCHW"):
data_format = data_format.upper() # supprt NHWC, nhwc, etc.
pool_type = pool_type.lower() # supprt max, Max, etc.
if pool_type not in ["max", "avg"]:
raise ValueError(
"Unknown pool_type: '%s'. It can only be 'max' or 'avg'.",
@ -820,6 +828,11 @@ class Pool2D(layers.Layer):
if not isinstance(use_cudnn, bool):
raise ValueError("use_cudnn should be True or False")
if data_format not in ["NCHW", "NHWC"]:
raise ValueError(
"Attr(data_format) should be 'NCHW' or 'NHWC'. Received "
"Attr(data_format): %s." % str(data_format))
super(Pool2D, self).__init__()
self._pool_type = pool_type
@ -831,6 +844,7 @@ class Pool2D(layers.Layer):
self._use_cudnn = use_cudnn
self._ceil_mode = ceil_mode
self._exclusive = exclusive
self._data_format = data_format
self._l_type = 'pool2d'
def forward(self, input):
@ -839,7 +853,8 @@ class Pool2D(layers.Layer):
'global_pooling', self._global_pooling, 'strides',
self._pool_stride, 'paddings', self._pool_padding,
'use_cudnn', self._use_cudnn, 'ceil_mode', self._ceil_mode,
'use_mkldnn', False, 'exclusive', self._exclusive)
'use_mkldnn', False, 'exclusive', self._exclusive,
'data_format', self._data_format)
return core.ops.pool2d(input, *attrs)
check_variable_and_dtype(
@ -856,6 +871,7 @@ class Pool2D(layers.Layer):
"ceil_mode": self._ceil_mode,
"use_mkldnn": False,
"exclusive": self._exclusive,
"data_format": self._data_format,
}
inputs = {"X": [input]}

2
python/paddle/fluid/layers/nn.py
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@ -1902,7 +1902,7 @@ def pool2d(input,
None by default.
exclusive (bool): Whether to exclude padding points in average pooling
mode, default is `true`.
data_format (string): The data format of the input and output data. An optional string from: `"NCHW"`, `"NDHW"`.
data_format (string): The data format of the input and output data. An optional string from: `"NCHW"`, `"NHWC"`.
The default is `"NCHW"`. When it is `"NCHW"`, the data is stored in the order of:
`[batch_size, input_channels, input_height, input_width]`.

72
python/paddle/fluid/tests/unittests/test_pool2d_op.py
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@ -1295,6 +1295,78 @@ class TestDygraphPool2DAPIError(unittest.TestCase):
name='x1', shape=[3, 32, 32, 5], dtype="int32")
self.assertRaises(TypeError, pool2d, data2)
def test_data_format_error(self):
with program_guard(Program(), Program()):
# the data_format must be 'NCHW' or 'NHWC'
data1 = np.random.random((3, 32, 32, 5)).astype('float32')
self.assertRaises(
ValueError,
fluid.dygraph.Pool2D,
pool_size=2,
pool_type='max',
pool_stride=1,
global_pooling=False,
data_format='NWHC')
class TestDygraphPool2DAPI(unittest.TestCase):
def test_nhwc(self):
with fluid.dygraph.guard():
data = np.random.random((3, 32, 32, 5)).astype('float32')
x = fluid.dygraph.to_variable(data)
pool2d = fluid.dygraph.Pool2D(
pool_size=2,
pool_type='max',
pool_stride=1,
pool_padding=[0, 0],
global_pooling=False,
data_format='NHWC')
out1 = pool2d(x)
out2 = pool2D_forward_naive(
data, [2, 2], [1, 1],
paddings=[0, 0],
pool_type='max',
data_format='NHWC')
self.assertTrue(np.allclose(out1.numpy(), out2))
def test_lower_case(self):
with fluid.dygraph.guard():
data = np.random.random((3, 32, 32, 5)).astype('float32')
x = fluid.dygraph.to_variable(data)
pool2d = fluid.dygraph.Pool2D(
pool_size=2,
pool_type='max',
pool_stride=1,
pool_padding=[0, 0],
global_pooling=False,
data_format='nhwc')
out1 = pool2d(x)
out2 = pool2D_forward_naive(
data, [2, 2], [1, 1],
paddings=[0, 0],
pool_type='max',
data_format='NHWC')
self.assertTrue(np.allclose(out1.numpy(), out2))
def test_upper_case(self):
with fluid.dygraph.guard():
data = np.random.random((3, 32, 32, 5)).astype('float32')
x = fluid.dygraph.to_variable(data)
pool2d = fluid.dygraph.Pool2D(
pool_size=2,
pool_type='MAX',
pool_stride=1,
pool_padding=[0, 0],
global_pooling=False,
data_format='nhwc')
out1 = pool2d(x)
out2 = pool2D_forward_naive(
data, [2, 2], [1, 1],
paddings=[0, 0],
pool_type='max',
data_format='NHWC')
self.assertTrue(np.allclose(out1.numpy(), out2))
if __name__ == '__main__':
unittest.main()

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