Data windowing

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Description

• tf.stack
  • NOTE: Given a list of length N of tensors of shape (A, B, C): If axis ==0 then the output tensor will have the shape (N, A, B, C). If axis ==1 then the output tensor will have the shape (A, N, B, C).
• tf.tile
  • NOTE: This operation creates a new tensor by replicating input multiples times. The output tensor's i'th dimension has input.dim(i) * multiples[i] elements, and the values of input are replicated multiples[i] times along the i'th dimension. For example, tiling [a b c d] by [2] produces [a b c d a b c d]

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Tensor

• Here is a "scalar" or "rank-0" tensor. A scalar contains a single value, and no "axes"
• A "vector" or "rank-1" tensor is like a list of values. A vector has one axis:
• A "matrix" or "rank-2" tensor has two axes:
• Here is a tensor with three axes:
• A "rank-4" tensor:
• Đọc thêm ở đây: tensor

  Axis

  

• axis= 0: là từ trên xuống dưới, nên tf.stack là xếp chồng từ trên xuống dưới
• axis=1: là từ trái qua phải, nên tf.stack là sắp xếp từ trái qua phải