systemml git commit: [MINOR] Add clarity to depthwise convolution documentation.

[du...@apache.org]

Repository: systemml
Updated Branches:
  refs/heads/master 6b25b3bf2 -> cbde17bab


[MINOR] Add clarity to depthwise convolution documentation.


Project: http://git-wip-us.apache.org/repos/asf/systemml/repo
Commit: http://git-wip-us.apache.org/repos/asf/systemml/commit/cbde17ba
Tree: http://git-wip-us.apache.org/repos/asf/systemml/tree/cbde17ba
Diff: http://git-wip-us.apache.org/repos/asf/systemml/diff/cbde17ba

Branch: refs/heads/master
Commit: cbde17babd2452c4f265e0b6c56296f246c007a4
Parents: 6b25b3b
Author: Mike Dusenberry <mw...@us.ibm.com>
Authored: Fri Jun 30 12:05:35 2017 -0700
Committer: Mike Dusenberry <mw...@us.ibm.com>
Committed: Fri Jun 30 12:05:35 2017 -0700

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 scripts/nn/layers/conv2d_depthwise.dml           |  4 ++++
 scripts/nn/layers/conv2d_transpose_depthwise.dml | 14 ++++++++++++++
 2 files changed, 18 insertions(+)
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http://git-wip-us.apache.org/repos/asf/systemml/blob/cbde17ba/scripts/nn/layers/conv2d_depthwise.dml
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diff --git a/scripts/nn/layers/conv2d_depthwise.dml b/scripts/nn/layers/conv2d_depthwise.dml
index 0e9abb5..ff36ea1 100644
--- a/scripts/nn/layers/conv2d_depthwise.dml
+++ b/scripts/nn/layers/conv2d_depthwise.dml
@@ -42,6 +42,10 @@ forward = function(matrix[double] X, matrix[double] W, matrix[double] b,
    * depth 1 that expand each input channel to M output channels, where
    * M is a "depth multiplier".
    *
+   * Although there are C*M filters of depth 1, instead of storing W as
+   * shape `(C*M, 1*Hf*Wf)`, we reshape it to `(C, M*Hf*Wf)` for
+   * performance reasons.
+   *
    * Inputs:
    *  - X: Inputs, of shape (N, C*Hin*Win).
    *  - W: Weights, of shape (C, M*Hf*Wf).

http://git-wip-us.apache.org/repos/asf/systemml/blob/cbde17ba/scripts/nn/layers/conv2d_transpose_depthwise.dml
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diff --git a/scripts/nn/layers/conv2d_transpose_depthwise.dml b/scripts/nn/layers/conv2d_transpose_depthwise.dml
index fdd7c10..b3e798c 100644
--- a/scripts/nn/layers/conv2d_transpose_depthwise.dml
+++ b/scripts/nn/layers/conv2d_transpose_depthwise.dml
@@ -41,6 +41,20 @@ forward = function(matrix[double] X, matrix[double] W, matrix[double] b,
    * The resulting C/M separate output channels are then concatenated
    * together channel-wise into a single volume of C/M output channels.
    *
+   * For clarity, if we were to use the same terminology as a regular
+   * depthwise convolution, a depthwise transpose convolution has the
+   * ability to contract each group of M input channels (from a total of
+   * C*M input channels) back to a single output channel, thus leading
+   * to C output channels.  Thus, this is the "transpose" of the regular
+   * depthwise convolution.  To keep the convention of always referring
+   * to the number of input channels as C, in this depthwise transpose
+   * layer we can reformulate the above by dividing by M.  With this
+   * reformulation, we can now state that there are C input channels,
+   * and for each group of M inputs we output a single output channel,
+   * for a total of C/M output channels.  For this, we use 1 filter of
+   * depth M for each group of M input channels, and we store W as
+   * `(C/M, M*Hf*Wf)`.
+   *
    * Inputs:
    *  - X: Inputs, of shape (N, C*Hin*Win).
    *  - W: Weights, of shape (C/M, M*Hf*Wf).