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This commit is contained in:
Dhairya Gandhi 2019-09-27 12:07:55 +05:30
parent 9f2ac8fdef
commit a801fcb9e7
1 changed files with 3 additions and 3 deletions
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6
src/layers/conv.jl
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@ -83,7 +83,7 @@ Standard convolutional transpose layer. `size` should be a tuple like `(2, 2)`.
Data should be stored in WHCN order. In other words, a 100×100 RGB image would
be a `100×100×3` array, and a batch of 50 would be a `100×100×3×50` array.
Takes the keyword arguments `pad`, `stride` and `dilation`.
Takes the keyword arguments `use_bias`, `pad`, `stride` and `dilation`.
"""
struct ConvTranspose{N,M,F,A,V}
σ::F
@ -158,7 +158,7 @@ Note that `out` must be an integer multiple of `in`.
Data should be stored in WHCN order. In other words, a 100×100 RGB image would
be a `100×100×3` array, and a batch of 50 would be a `100×100×3×50` array.
Takes the keyword arguments `pad`, `stride` and `dilation`.
Takes the keyword arguments `use_bias`, `pad`, `stride` and `dilation`.
"""
struct DepthwiseConv{N,M,F,A,V}
σ::F
@ -236,7 +236,7 @@ Data should be stored in WHCN order (width, height, # channels, # batches).
In other words, a 100×100 RGB image would be a `100×100×3×1` array,
and a batch of 50 would be a `100×100×3×50` array.
Takes the keyword arguments `pad`, `stride` and `dilation`.
Takes the keyword arguments `use_bias`, `pad`, `stride` and `dilation`.
"""
struct CrossCor{N,M,F,A,V}
σ::F