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TensorFlow: tf.nn.conv2d
Computes a 2-D convolution given input and 4-D filters tensors. tf.nn.conv2d( input, filters, strides, padding, data_format='NHWC', dilations=None, name=None ) 1.input: A Tensor. Must be one of the following types: half, bfloat16, float32, float64. A Tensor of rank at least 4. The dimension order is interpreted according to the value of data_format; with the all-but-inner-3 dimensions acting as batch dimensions. See below for details.
2.filters: A Tensor. Must have the same type as input. A 4-D tensor of shape [filter_height, filter_width, in_channels, out_channels]
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strides An int or list of ints that has length 1, 2 or 4. The stride of the sliding window for each dimension of input. If a single value is given it is replicated in the H and W dimension. By default the N and C dimensions are set to 1. The dimension order is determined by the value of data_format, see below for details.
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padding Either the string "SAME" or "VALID" indicating the type of padding algorithm to use, or a list indicating the explicit paddings at the start and end of each dimension. When explicit padding is used and data_format is "NHWC", this should be in the form [[0, 0], [pad_top,pad_bottom], [pad_left, pad_right], [0, 0]]. When explicit padding used and data_format is "NCHW", this should be in the form [[0, 0], [0, 0],[pad_top, pad_bottom], [pad_left, pad_right]].
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data_format An optional string from: "NHWC", "NCHW". Defaults to "NHWC". Specify the data format of the input and output data. With the default format "NHWC", the data is stored in the order of: batch_shape + [height, width, channels]. Alternatively, the format could be "NCHW", the data storage order of: batch_shape + [channels, height, width].
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dilations An int or list of ints that has length 1, 2 or 4, defaults to 1. The dilation factor for each dimension ofinput. If a single value is given it is replicated in the H and W dimension. By default the N and C dimensions are set to 1. If set to k > 1, there will be k-1 skipped cells between each filter element on that dimension. The dimension order is determined by the value of data_format, see above for details. Dilations in the batch and depth dimensions if a 4-d tensor must be 1.
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name A name for the operation (optional).
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