- +

torch.nn¶

@@ -6716,7 +6716,7 @@

avg_pool1davg_pool2d ¶

-torch.nn.functional.avg_pool2d(input, kernel_size, stride=None, padding=0, ceil_mode=False, count_include_pad=True) → Variable¶: Applies 2D average-pooling operation in kh x kw regions by step size dh x dw steps. The number of output features is equal to the number of input planes.
@@ -6736,12 +6736,16 @@
avg_pool2dFalse
count_include_pad – when True, will include the zero-padding in th -averaging calculation. Default: True
+averaging calculation. Default: False +
+
Warning
+
Default value for count_include_pad was True in versions before 0.3, and will be changed back to True from 0.4.1 and forward.
+

@@ -6749,7 +6753,7 @@

avg_pool2d avg_pool3d ¶

-torch.nn.functional.avg_pool3d(input, kernel_size, stride=None, padding=0, ceil_mode=False, count_include_pad=True) → Variable¶: Applies 3D average-pooling operation in kt x kh x kw regions by step size dt x dh x dw steps. The number of output features is equal to the number of input planes / dt.
@@ -6769,12 +6773,16 @@
avg_pool3dFalse +
+
Warning
+
Default value for count_include_pad was True in versions before 0.3, and will be changed back to True from 0.4.1 and forward.
+

@@ -8435,20 +8443,20 @@

Parameters:	sort_by (str, optional) – Attribute used to sort entries. By default +they are printed in the same order as they were registered. +Valid keys include: `cpu_time`, `cuda_time`, `cpu_time_total`, +`cuda_time_total`, `count`.
Returns:	A string containing the table.

Parameters:	+ function – describes what to run in the forward pass of the model or +part of the model. It should also know how to handle the inputs +passed as the tuple. For example, in LSTM, if user passes +`(activation, hidden)`, `function` should correctly use the +first input as `activation` and the second input as `hidden` + args – tuple containing inputs to the `function` + +
Returns:	attr`function` on *`args` +
Return type:	Output of running +

Parameters:	+ functions – A `torch.nn.Sequential` or the list of modules or +functions (comprising the model) to run sequentially. + segments – Number of chunks to create in the model + inputs – tuple of Tensors that are inputs to `functions` + +
Returns:	Output of running `functions` sequentially on *`inputs` +

Parameters:	cuda – If True, includes CUDA-specific include paths.
Returns:	A list of include path strings.

Parameters:	compiler (str) – The compiler executable name to check (e.g. `g++`). +Must be executable in a shell process.
Returns:	False if the compiler is (likely) ABI-incompatible with PyTorch, +else True.

Parameters:	device (int) – device for which to return the name. This function is a +no-op if this argument is negative.
Returns:	the major and minor cuda capability of the device
Return type:	tuple(int, int)

Parameters:	+ tensor (Tensor) – tensor to broadcast. + devices (Iterable) – an iterable of devices among which to broadcast. +Note that it should be like (src, dst1, dst2, ...), the first element +of which is the source device to broadcast from. + +
Returns:	A tuple containing copies of the `tensor`, placed on devices +corresponding to indices from `devices`. +

Parameters:	+ tensors (sequence) – tensors to broadcast. + devices (Iterable) – an iterable of devices among which to broadcast. +Note that it should be like (src, dst1, dst2, ...), the first element +of which is the source device to broadcast from. + buffer_size (int) – maximum size of the buffer used for coalescing + +
Returns:	A tuple containing copies of the `tensor`, placed on devices +corresponding to indices from `devices`. +

Parameters:	+ inputs (Iterable[Tensor]) – an iterable of tensors to add. + destination (int, optional) – a device on which the output will be +placed (default: current device). + +
Returns:	A tensor containing an elementwise sum of all inputs, placed on the +`destination` device. +

torch.nn¶

avg_pool1davg_pool2d¶

avg_pool2davg_pool3d¶

avg_pool3dFalse + +Warning +Default value for count_include_pad was True in versions before 0.3, and will be changed back to True from 0.4.1 and forward. +

torch.nn.init - +

torch.nn¶

avg_pool1davg_pool2d¶

avg_pool2davg_pool3d¶

avg_pool3dFalse + +Warning +Default value for count_include_pad was True in versions before 0.3, and will be changed back to True from 0.4.1 and forward. +

torch.nn.init - + Next - - + + Previous - +

torch.nn.initSphinx using a theme provided by Read the Docs. + Built with Sphinx using a theme provided by Read the Docs. @@ -8541,10 +8549,10 @@

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avg_pool1davg_pool2d ¶

avg_pool2d avg_pool3d ¶

avg_pool3dFalse +
+
Warning
+
Default value for `count_include_pad` was `True` in versions before 0.3, and will be changed back to `True` from 0.4.1 and forward.
+

avg_pool1davg_pool2d ¶

avg_pool2d avg_pool3d ¶

avg_pool3dFalse +
+
Warning
+
Default value for `count_include_pad` was `True` in versions before 0.3, and will be changed back to `True` from 0.4.1 and forward.
+