[API 2.0] add functional pool1d API by LDOUBLEV · Pull Request #26108 · PaddlePaddle/Paddle

LDOUBLEV · 2020-08-10T14:21:22Z

PR types

New features

PR changes

APIs

Describe

add functional APIs:

paddle.nn.functional.avg_pool1d
paddle.nn.functional.max_pool1d
paddle.nn.functional.adaptive_avg_pool1d
paddle.nn.functional.adaptive_max_pool1d
paddle.nn.AvgPool1d
paddle.nn.MaxPool1d
paddle.nn.AdaptiveAvgPool1d
paddle.nn.AdaptiveMaxPool1d

paddle-bot-old · 2020-08-10T14:21:32Z

Thanks for your contribution!
Please wait for the result of CI firstly. See Paddle CI Manual for details.

paddle-bot-old · 2020-08-10T14:21:34Z

✅ This PR's description meets the template requirements!
Please wait for other CI results.

… develop

littletomatodonkey · 2020-08-11T06:18:42Z

python/paddle/fluid/tests/unittests/test_pool1d_op.py

+
+
+def adaptive_start_index(index, input_size, output_size):
+    return int(np.floor(index * input_size / output_size))


直接int就可以？

为了和ceil mode区分

littletomatodonkey · 2020-08-11T06:19:29Z

python/paddle/fluid/tests/unittests/test_pool1d_op.py

+    return int(np.ceil((index + 1) * input_size / output_size))
+
+
+def max_pool1D_forward_naive(x,


pool1D -> pool1d ?

littletomatodonkey · 2020-08-11T06:20:19Z

python/paddle/fluid/tests/unittests/test_pool1d_op.py

+def test_np_pd_pool1d():
+    data = np.random.random((2, 4, 32)).astype('float32')
+    with fluid.dygraph.guard():
+        # datapd = fluid.layers.assign(data)


comment删掉？

python/paddle/fluid/tests/unittests/test_pool1d_op.py

littletomatodonkey · 2020-08-11T06:20:53Z

python/paddle/fluid/tests/unittests/test_pool1d_op.py

+            data, ksize=[6], adaptive=True, paddings=[0], strides=[0])
+
+    np.testing.assert_allclose(res_np, res_pd.numpy())
+    print("=> unittest adaptive_avg_pool1d success!")


littletomatodonkey · 2020-08-11T06:21:57Z

python/paddle/nn/functional/pooling.py

+
+          import paddle.fluid as fluid
+
+          data = fluid.data(name='data', shape=[None, 3, 32], dtype='float32')


paddle.data?2.0好像主要用paddle.了

应该还是fluid.data，可以再确认下

littletomatodonkey · 2020-08-11T06:22:14Z

python/paddle/nn/functional/pooling.py

+          data = fluid.data(name='data', shape=[None, 3, 32], dtype='float32')
+
+          # max pool2d
+          pool2d = fluid.layers.functional.avg_pool1d(input=data, kernel_size=2, stride=2, padding=0)


paddle.nn.functional

WuHaobo · 2020-08-18T08:14:44Z

python/paddle/nn/functional/pooling.py

+               stride=None,
+               padding=0,
+               count_include_pad=True,
+               ceil_mode=False,


data_format='NCL'

WuHaobo · 2020-08-18T08:15:26Z

python/paddle/nn/functional/pooling.py

+                             None by default.
+        count_include_pad (bool): Whether to exclude padding points in average pooling
+                          mode, default is `true`.
+


Args 顺序，name最后一个

WuHaobo · 2020-08-18T08:16:59Z

python/paddle/nn/functional/pooling.py

+               stride=None,
+               padding=0,
+               ceil_mode=False,
+               return_indices=False,


return_indices=False, ceil_mode=False, data_format='NCL'

WuHaobo · 2020-08-18T08:18:22Z

python/paddle/nn/layer/common.py

+                 stride=None,
+                 padding=0,
+                 ceil_mode=False,
+                 count_include_pad=True):


dataformat name

… develop

WuHaobo

LGTM

shippingwang · 2020-08-20T14:35:26Z

python/paddle/nn/layer/common.py

    'Linear',
    'UpSample',
    'Pad2D',
+    'AvgPool1d',


move pool layer to layer/pooling.py ?

目前是都在common.py里的

shippingwang · 2020-08-20T14:41:51Z

python/paddle/nn/functional/pooling.py

+    Args:
+        x (Tensor): The input tensor of pooling operator which is a 3-D tensor with
+                          shape [N, C, L]. The format of input tensor is `"NCL"` or
+                          `"NHL"`, where `N` is batch size, `C` is the number of channels,


dataformat 低优

shippingwang · 2020-08-20T14:46:50Z

python/paddle/nn/functional/pooling.py

+
+    """
+    """NCL to NCHW"""
+    data_format = "NCHW"


shippingwang · 2020-08-20T14:49:12Z

python/paddle/nn/functional/pooling.py

+            padding_algorithm, 'use_cudnn', not count_include_pad, 'ceil_mode',
+            ceil_mode, 'use_mkldnn', False, 'exclusive', True, 'data_format',
+            data_format)
+        return squeeze(output, [2])


call core.ops.squeeze?

shippingwang · 2020-08-20T14:49:58Z

python/paddle/nn/functional/pooling.py

+    Args:
+        x (Tensor): The input tensor of pooling operator which is a 3-D tensor with
+                          shape [N, C, L]. The format of input tensor is `"NCL"` or
+                          `"NHL"`, where `N` is batch size, `C` is the number of channels,


shippingwang · 2020-08-20T15:04:47Z

python/paddle/nn/functional/pooling.py

+
+def check_input(x, dimension):
+    if len(x.shape) != dimension:
+        raise ValueError("Excepted Input X is 3-D tensor, but received {}-D {}".


dimension - D

shippingwang · 2020-08-20T16:47:56Z

python/paddle/nn/functional/pooling.py

+    """
+    """NCL to NCHW"""
+    data_format = "NCHW"
+    check_variable_and_dtype(x, 'input', ['float32', 'float64'], 'avg_pool1d')


if not in_dygraph_mode

适用静态图模式

shippingwang · 2020-08-20T18:09:16Z

python/paddle/nn/layer/common.py

+                             None by default.
+    Returns:
+        None.
+


返回的是一个对象

shippingwang · 2020-08-20T18:21:27Z

python/paddle/nn/layer/common.py

+          # pool_out shape: [1, 3, 16]
+
+          # for return_indices = true
+          AdaptiveMaxPool1d = nn.AdaptiveMaxPool1d(output_size=16, return_indices=True)


use lower name name function

shippingwang · 2020-08-20T18:25:07Z

python/paddle/nn/layer/common.py

+
+       Output(i) &= max(Input[lstart:lend])}
+
+    Args:


shippingwang · 2020-08-20T18:38:28Z

python/paddle/nn/functional/pooling.py

+                                 None by default.
+
+        Returns:
+            Tensor: The output tensor of adaptive pooling result. The data type is same


There are two conditions

LDOUBLEV · 2020-08-21T02:43:48Z

为了防止PR合入冲突，将该PR 的修改合并到 #26331 中，此PR可关闭

paddle-bot-old · 2021-09-14T09:01:51Z

Since you haven't replied for more than a year, we have closed this issue/pr.
If the problem is not solved or there is a follow-up one, please reopen it at any time and we will continue to follow up.
由于您超过一年未回复，我们将关闭这个issue/pr。
若问题未解决或有后续问题，请随时重新打开，我们会继续跟进。

add functional pool1d API,test=develop

6505ef5

LDOUBLEV added 2 commits August 11, 2020 03:08

Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…

70e28b4

… develop

add unittest and import,test=develop

4bd0c6b

littletomatodonkey reviewed Aug 11, 2020

View reviewed changes

LDOUBLEV added 5 commits August 11, 2020 07:25

add paddle.nn Pool1D API,test=develop

62d8f8c

using paddle.nn, test=develop

afa5add

fix unittest case, test=develop

b702df7

Pool1D 2 Pool1d,test=develop

f6cdf8f

fix doc and corresponding code,test=develop

361ab8f

LDOUBLEV changed the title ~~add functional pool1d API~~ [API 2.0] add functional pool1d API Aug 17, 2020

LDOUBLEV added 2 commits August 18, 2020 07:20

fix low coverage; to_variable to to_tensor,test=develop

7d8520a

fix low coverage; to_variable to to_tensor,test=develop

60194d4

WuHaobo reviewed Aug 18, 2020

View reviewed changes

python/paddle/nn/layer/common.py Outdated

stride=None,

padding=0,

ceil_mode=False,

count_include_pad=True):

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WuHaobo Aug 18, 2020

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dataformat name

LDOUBLEV added 4 commits August 19, 2020 02:26

Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…

28c725b

… develop

sort params, Variable to tensor, test=develop

06fe2fd

fix padding bug, test=develop

49a374d

fix conflicts,test=develop

60247db

WuHaobo approved these changes Aug 20, 2020

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shippingwang reviewed Aug 20, 2020

View reviewed changes

python/paddle/nn/layer/common.py

Output(i) &= max(Input[lstart:lend])}

Args:

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Parameters

shippingwang reviewed Aug 20, 2020

View reviewed changes

paddle-bot-old bot closed this Sep 14, 2021



		def adaptive_start_index(index, input_size, output_size):
		return int(np.floor(index * input_size / output_size))

		return int(np.ceil((index + 1) * input_size / output_size))


		def max_pool1D_forward_naive(x,


		import paddle.fluid as fluid

		data = fluid.data(name='data', shape=[None, 3, 32], dtype='float32')

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LDOUBLEV commented Aug 21, 2020

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LDOUBLEV commented Aug 10, 2020 •

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