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@ -111,14 +111,14 @@ class Conv2d(_Conv):
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2D convolution layer.
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2D convolution layer.
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Applies a 2D convolution over an input tensor which is typically of shape :math:`(N, C_{in}, H_{in}, W_{in})`,
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Applies a 2D convolution over an input tensor which is typically of shape :math:`(N, C_{in}, H_{in}, W_{in})`,
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where :math:`N` is batch size and :math:`C_{in}` is channel number. For each batch of shape
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where :math:`N` is batch size, :math:`C_{in}` is channel number, and :math:`H_{in}, W_{in})` are height and width.
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:math:`(C_{in}, H_{in}, W_{in})`, the formula is defined as:
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For each batch of shape :math:`(C_{in}, H_{in}, W_{in})`, the formula is defined as:
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.. math::
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.. math::
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out_j = \sum_{i=0}^{C_{in} - 1} ccor(W_{ij}, X_i) + b_j,
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out_j = \sum_{i=0}^{C_{in} - 1} ccor(W_{ij}, X_i) + b_j,
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where :math:`ccor` is the cross correlation operator, :math:`C_{in}` is the input channel number, :math:`j` ranges
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where :math:`ccor` is the cross-correlation operator, :math:`C_{in}` is the input channel number, :math:`j` ranges
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from :math:`0` to :math:`C_{out} - 1`, :math:`W_{ij}` corresponds to the :math:`i`-th channel of the :math:`j`-th
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from :math:`0` to :math:`C_{out} - 1`, :math:`W_{ij}` corresponds to the :math:`i`-th channel of the :math:`j`-th
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filter and :math:`out_{j}` corresponds to the :math:`j`-th channel of the output. :math:`W_{ij}` is a slice
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filter and :math:`out_{j}` corresponds to the :math:`j`-th channel of the output. :math:`W_{ij}` is a slice
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of kernel and it has shape :math:`(\text{ks_h}, \text{ks_w})`, where :math:`\text{ks_h}` and
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of kernel and it has shape :math:`(\text{ks_h}, \text{ks_w})`, where :math:`\text{ks_h}` and
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@ -162,8 +162,8 @@ class Conv2d(_Conv):
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Tensor borders. `padding` should be greater than or equal to 0.
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Tensor borders. `padding` should be greater than or equal to 0.
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padding (Union[int, tuple[int]]): Implicit paddings on both sides of the input. If `padding` is one integer,
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padding (Union[int, tuple[int]]): Implicit paddings on both sides of the input. If `padding` is one integer,
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the padding of top, bottom, left and right is the same, equal to padding. If `padding` is a tuple
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the paddings of top, bottom, left and right are the same, equal to padding. If `padding` is a tuple
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with four integers, the padding of top, bottom, left and right will be equal to padding[0],
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with four integers, the paddings of top, bottom, left and right will be equal to padding[0],
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padding[1], padding[2], and padding[3] accordingly. Default: 0.
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padding[1], padding[2], and padding[3] accordingly. Default: 0.
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dilation (Union[int, tuple[int]]): The data type is int or a tuple of 2 integers. Specifies the dilation rate
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dilation (Union[int, tuple[int]]): The data type is int or a tuple of 2 integers. Specifies the dilation rate
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to use for dilated convolution. If set to be :math:`k > 1`, there will
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to use for dilated convolution. If set to be :math:`k > 1`, there will
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@ -472,8 +472,8 @@ class Conv2dTranspose(_Conv):
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- valid: Adopted the way of discarding.
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- valid: Adopted the way of discarding.
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padding (Union[int, tuple[int]]): Implicit paddings on both sides of the input. If `padding` is one integer,
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padding (Union[int, tuple[int]]): Implicit paddings on both sides of the input. If `padding` is one integer,
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the padding of top, bottom, left and right is the same, equal to padding. If `padding` is a tuple
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the paddings of top, bottom, left and right are the same, equal to padding. If `padding` is a tuple
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with four integers, the padding of top, bottom, left and right will be equal to padding[0],
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with four integers, the paddings of top, bottom, left and right will be equal to padding[0],
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padding[1], padding[2], and padding[3] accordingly. Default: 0.
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padding[1], padding[2], and padding[3] accordingly. Default: 0.
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dilation (Union[int, tuple[int]]): The data type is int or a tuple of 2 integers. Specifies the dilation rate
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dilation (Union[int, tuple[int]]): The data type is int or a tuple of 2 integers. Specifies the dilation rate
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to use for dilated convolution. If set to be :math:`k > 1`, there will
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to use for dilated convolution. If set to be :math:`k > 1`, there will
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@ -856,8 +856,8 @@ class DepthwiseConv2d(Cell):
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Tensor borders. `padding` should be greater than or equal to 0.
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Tensor borders. `padding` should be greater than or equal to 0.
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padding (Union[int, tuple[int]]): Implicit paddings on both sides of the input. If `padding` is one integer,
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padding (Union[int, tuple[int]]): Implicit paddings on both sides of the input. If `padding` is one integer,
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the padding of top, bottom, left and right is the same, equal to padding. If `padding` is a tuple
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the paddings of top, bottom, left and right are the same, equal to padding. If `padding` is a tuple
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with four integers, the padding of top, bottom, left and right will be equal to padding[0],
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with four integers, the paddings of top, bottom, left and right will be equal to padding[0],
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padding[1], padding[2], and padding[3] accordingly. Default: 0.
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padding[1], padding[2], and padding[3] accordingly. Default: 0.
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dilation (Union[int, tuple[int]]): The data type is int or a tuple of 2 integers. Specifies the dilation rate
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dilation (Union[int, tuple[int]]): The data type is int or a tuple of 2 integers. Specifies the dilation rate
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to use for dilated convolution. If set to be :math:`k > 1`, there will
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to use for dilated convolution. If set to be :math:`k > 1`, there will
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mindspore-ci-bot
5 years ago
committed by
Gitee