From 0ca29943bccd02f50c20fb7118b048f3abcc2fc7 Mon Sep 17 00:00:00 2001 From: =?utf8?q?=EB=82=A8=EA=B6=81=EC=84=9D/=EB=8F=99=EC=9E=91=EC=A0=9C?= =?utf8?q?=EC=96=B4Lab=28SR=29/Engineer/=EC=82=BC=EC=84=B1=EC=A0=84?= =?utf8?q?=EC=9E=90?= Date: Tue, 11 Dec 2018 09:39:47 +0900 Subject: [PATCH] [tflchef] Update README and related test (#2430) This commit will introduce gaussian filler in tflchef And also recipe of readme will be modified Signed-off-by: Seok NamKoong --- contrib/tflchef/README.md | 7 ++++++- contrib/tflchef/tests/readme/test.recipe | 5 +++++ 2 files changed, 11 insertions(+), 1 deletion(-) diff --git a/contrib/tflchef/README.md b/contrib/tflchef/README.md index 7d680e8..c940f22 100644 --- a/contrib/tflchef/README.md +++ b/contrib/tflchef/README.md @@ -10,7 +10,7 @@ Given a recipe, _tflchef_ will cook a tensorflow lite model for you. ## Tutorial: How to use? This example explains how to generate a tensorflow lite model with a single Conv2D operation -with constant (1.1f) bias with _tflchef_. +with a kernel filled with random values generated according to normal (or gaussian) distribution (mean = 0.0f / stddev = 1.0f) and bias with constant values (1.1f) with _tflchef_. The first step is to write a recipe! Type the following command, and then you may get ``sample.recipe``: @@ -25,6 +25,11 @@ operand { name: "ker" type: FLOAT32 shape { dim: 1 dim: 1 dim: 1 dim: 2 } + filler { + tag: "gaussian" + arg: "0.0" + arg: "1.0" + } } operand { name: "bias" diff --git a/contrib/tflchef/tests/readme/test.recipe b/contrib/tflchef/tests/readme/test.recipe index 36e13d3..bc41a3f 100644 --- a/contrib/tflchef/tests/readme/test.recipe +++ b/contrib/tflchef/tests/readme/test.recipe @@ -7,6 +7,11 @@ operand { name: "ker" type: FLOAT32 shape { dim: 1 dim: 1 dim: 1 dim: 2 } + filler { + tag: "gaussian" + arg: "0.0" + arg: "1.0" + } } operand { name: "bias" -- 2.7.4