From: 박천교/On-Device Lab(SR)/Engineer/삼성전자 <ch.bahk@samsung.com>
Date: Thu, 22 Aug 2019 10:05:32 +0000 (+0900)
Subject: [res] Remove renamed inception tests (#6838)
X-Git-Tag: accepted/tizen/unified/20190903.052428~196
X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=fbaed6bc2c7be10f9974711b80259b5e3e6adda0;p=platform%2Fcore%2Fml%2Fnnfw.git

[res] Remove renamed inception tests (#6838)

TF_IV3_XXXX tests are fully replaced by NET_0017~0021. These renamed
tests are safely removed by this commit.

Signed-off-by: Cheongyo Bahk <ch.bahk@samsung.com>
---

diff --git a/res/TensorFlowTests/TF_IV3_AvgPool_GlobalPooling/test.info b/res/TensorFlowTests/TF_IV3_AvgPool_GlobalPooling/test.info
deleted file mode 100644
index e9413cb..0000000
--- a/res/TensorFlowTests/TF_IV3_AvgPool_GlobalPooling/test.info
+++ /dev/null
@@ -1,2 +0,0 @@
-input,  placeholder:0, TF_FLOAT, [1, 8, 8, 1]
-output, avgpool2d:0,   TF_FLOAT, [1, 1, 1, 1]
diff --git a/res/TensorFlowTests/TF_IV3_AvgPool_GlobalPooling/test.pbtxt b/res/TensorFlowTests/TF_IV3_AvgPool_GlobalPooling/test.pbtxt
deleted file mode 100644
index e8cc76b..0000000
--- a/res/TensorFlowTests/TF_IV3_AvgPool_GlobalPooling/test.pbtxt
+++ /dev/null
@@ -1,61 +0,0 @@
-# HOW TO GENERATE:
-#
-#  import tensorflow as tf
-#  value = tf.placeholder(dtype=tf.float32, shape=[1, 8, 8, 1], name='placeholder')
-#  output = tf.nn.avg_pool(value, [1, 8, 8, 1], [1, 1, 1, 1], 'VALID', name='avgpool2d')
-#  tf.get_default_graph().as_graph_def()
-#
-# NOTE 1. The output shape is 1x1x1x1
-#
-# >>> tf.graph_util.tensor_shape_from_node_def_name(tf.get_default_graph(), 'avgpool2d')
-# TensorShape([Dimension(1), Dimension(1), Dimension(1), Dimension(1)])
-#
-# NOTE 2. This test corresponds to the last AvgPool node inception v3 2018.04.27.
-node {
-  name: "placeholder"
-  op: "Placeholder"
-  attr {
-    key: "dtype"
-    value { type: DT_FLOAT }
-  }
-  attr {
-    key: "shape"
-    value {
-      shape {
-        dim { size: 1 }
-        dim { size: 8 }
-        dim { size: 8 }
-        dim { size: 1 }
-      }
-    }
-  }
-}
-node {
-  name: "avgpool2d"
-  op: "AvgPool"
-  input: "placeholder"
-  attr {
-    key: "T"
-    value { type: DT_FLOAT }
-  }
-  attr {
-    key: "data_format"
-    value { s: "NHWC" }
-  }
-  attr {
-    key: "ksize"
-    value {
-      list { i: 1 i: 8 i: 8 i: 1 }
-    }
-  }
-  attr {
-    key: "padding"
-    value { s: "VALID" }
-  }
-  attr {
-    key: "strides"
-    value {
-      list { i: 1 i: 1 i: 1 i: 1 }
-    }
-  }
-}
diff --git a/res/TensorFlowTests/TF_IV3_AvgPool_Module/test.info b/res/TensorFlowTests/TF_IV3_AvgPool_Module/test.info
deleted file mode 100644
index 87f6fa7..0000000
--- a/res/TensorFlowTests/TF_IV3_AvgPool_Module/test.info
+++ /dev/null
@@ -1,2 +0,0 @@
-input,  placeholder:0, TF_FLOAT, [1, 4, 4, 1]
-output, avgpool2d:0,   TF_FLOAT, [1, 4, 4, 1]
diff --git a/res/TensorFlowTests/TF_IV3_AvgPool_Module/test.pbtxt b/res/TensorFlowTests/TF_IV3_AvgPool_Module/test.pbtxt
deleted file mode 100644
index 3b8a15e..0000000
--- a/res/TensorFlowTests/TF_IV3_AvgPool_Module/test.pbtxt
+++ /dev/null
@@ -1,63 +0,0 @@
-# HOW TO GENERATE:
-#
-#  import tensorflow as tf
-#  value = tf.placeholder(dtype=tf.float32, shape=[1, 4, 4, 1], name='placeholder')
-#  output = tf.nn.avg_pool(value, [1, 3, 3, 1], [1, 1, 1, 1], 'SAME', name='avgpool2d')
-#  tf.get_default_graph().as_graph_def()
-#
-# NOTE 1. The output shape is 1x4x4x1
-#
-# >>> tf.graph_util.tensor_shape_from_node_def_name(tf.get_default_graph(), 'avgpool2d')
-# TensorShape([Dimension(1), Dimension(4), Dimension(4), Dimension(1)])
-#
-# NOTE 2. Almost all the AvgPool nodes in inception v3 2018.04.27 use this configuration.
-#
-# The only exception is "InceptionV3/Logits/AvgPool_1a_8x8/AvgPool" which performs global average pooling.
-node {
-  name: "placeholder"
-  op: "Placeholder"
-  attr {
-    key: "dtype"
-    value { type: DT_FLOAT }
-  }
-  attr {
-    key: "shape"
-    value {
-      shape {
-        dim { size: 1 }
-        dim { size: 4 }
-        dim { size: 4 }
-        dim { size: 1 }
-      }
-    }
-  }
-}
-node {
-  name: "avgpool2d"
-  op: "AvgPool"
-  input: "placeholder"
-  attr {
-    key: "T"
-    value { type: DT_FLOAT }
-  }
-  attr {
-    key: "data_format"
-    value { s: "NHWC" }
-  }
-  attr {
-    key: "ksize"
-    value {
-      list { i: 1 i: 3 i: 3 i: 1 }
-    }
-  }
-  attr {
-    key: "padding"
-    value { s: "SAME" }
-  }
-  attr {
-    key: "strides"
-    value {
-      list { i: 1 i: 1 i: 1 i: 1 }
-    }
-  }
-}
diff --git a/res/TensorFlowTests/TF_IV3_Conv2D_000/test.info b/res/TensorFlowTests/TF_IV3_Conv2D_000/test.info
deleted file mode 100644
index 9088834..0000000
--- a/res/TensorFlowTests/TF_IV3_Conv2D_000/test.info
+++ /dev/null
@@ -1,2 +0,0 @@
-input,  ifm:0,  TF_FLOAT,  [1, 7, 7, 4]
-output, ofm:0,  TF_FLOAT,  [1, 3, 3, 6]
diff --git a/res/TensorFlowTests/TF_IV3_Conv2D_000/test.pbtxt b/res/TensorFlowTests/TF_IV3_Conv2D_000/test.pbtxt
deleted file mode 100644
index 076f4f6..0000000
--- a/res/TensorFlowTests/TF_IV3_Conv2D_000/test.pbtxt
+++ /dev/null
@@ -1,89 +0,0 @@
-# HOW TO GENERATE:
-#
-#  import tensorflow as tf
-#  I = 4
-#  O = 6
-#  ifm = tf.placeholder(dtype=tf.float32, shape=[1, 7, 7, I], name='ifm')
-#  ker = tf.constant(dtype=tf.float32, shape=[3, 3, I, O], name='ker', value=1.1)
-#  ofm = tf.nn.conv2d(input=ifm, filter=ker, strides=[1, 2, 2, 1], padding='VALID', name='ofm')
-#  tf.get_default_graph().as_graph_def()
-#
-# NOTE 1. The output shape is 1x3x3x6
-#
-# >>> tf.graph_util.tensor_shape_from_node_def_name(tf.get_default_graph(), 'ofm')
-# TensorShape([Dimension(1), Dimension(3), Dimension(3), Dimension(6)])
-#
-# NOTE 2. This test corresponds to "InceptionV3/InceptionV3/Conv2d_1a_3x3/Conv2D" node
-#
-node {
-  name: "ifm"
-  op: "Placeholder"
-  attr {
-    key: "dtype"
-    value { type: DT_FLOAT }
-  }
-  attr {
-    key: "shape"
-    value {
-      shape {
-        dim { size: 1 }
-        dim { size: 7 }
-        dim { size: 7 }
-        dim { size: 4 }
-      }
-    }
-  }
-}
-node {
-  name: "ker"
-  op: "Const"
-  attr {
-    key: "dtype"
-    value { type: DT_FLOAT }
-  }
-  attr {
-    key: "value"
-    value {
-      tensor {
-        dtype: DT_FLOAT
-        tensor_shape {
-          dim { size: 3 }
-          dim { size: 3 }
-          dim { size: 4 }
-          dim { size: 6 }
-        }
-        float_val: 1.1
-      }
-    }
-  }
-}
-node {
-  name: "ofm"
-  op: "Conv2D"
-  input: "ifm"
-  input: "ker"
-  attr {
-    key: "T"
-    value { type: DT_FLOAT }
-  }
-  attr {
-    key: "data_format"
-    value { s: "NHWC" }
-  }
-  attr {
-    key: "dilations"
-    value {
-      list { i: 1 i: 1 i: 1 i: 1 }
-    }
-  }
-  attr {
-    key: "padding"
-    value { s: "VALID" }
-  }
-  attr {
-    key: "strides"
-    value {
-      list { i: 1 i: 2 i: 2 i: 1 }
-    }
-  }
-}
diff --git a/res/TensorFlowTests/TF_IV3_Epilogue/test.info b/res/TensorFlowTests/TF_IV3_Epilogue/test.info
deleted file mode 100644
index d3ea85a..0000000
--- a/res/TensorFlowTests/TF_IV3_Epilogue/test.info
+++ /dev/null
@@ -1,2 +0,0 @@
-input,  placeholder:0,  TF_FLOAT,   [2, 1, 1, 3]
-output, reshape_2:0,    TF_FLOAT,   [2, 3]
diff --git a/res/TensorFlowTests/TF_IV3_Epilogue/test.pbtxt b/res/TensorFlowTests/TF_IV3_Epilogue/test.pbtxt
deleted file mode 100644
index efd18d1..0000000
--- a/res/TensorFlowTests/TF_IV3_Epilogue/test.pbtxt
+++ /dev/null
@@ -1,112 +0,0 @@
-# The Epilogue, or endmost part of inception v3 comprised of Squeeze,
-# Reshape, Shape and Softmax
-#
-# Only difference from original is input shape:
-#   - original has unknown batch and 1001 channels [?, 1, 1, 1001]
-#   - this test has 2 batches and 3 channels [2, 1, 1, 3]
-
-node {
-  name: "placeholder"
-  op: "Placeholder"
-  attr {
-    key: "dtype"
-    value { type: DT_FLOAT }
-  }
-  attr {
-    key: "shape"
-    value {
-      shape {
-        dim { size: 2 }
-        dim { size: 1 }
-        dim { size: 1 }
-        dim { size: 3 }
-      }
-    }
-  }
-}
-node {
-  name: "squeeze"
-  op: "Squeeze"
-  input: "placeholder"
-  attr {
-    key: "T"
-    value { type: DT_FLOAT }
-  }
-  attr {
-    key: "squeeze_dims"
-    value {
-      list { i: 1 i: 2 }
-    }
-  }
-}
-node {
-  name: "Reshape/shape"
-  op: "Const"
-  attr {
-    key: "dtype"
-    value { type: DT_INT32 }
-  }
-  attr {
-    key: "value"
-    value {
-      tensor {
-        dtype: DT_INT32
-        tensor_shape {
-          dim { size: 2 }
-        }
-        int_val: -1
-        int_val: 3
-      }
-    }
-  }
-}
-node {
-  name: "reshape_1"
-  op: "Reshape"
-  input: "squeeze"
-  input: "Reshape/shape"
-  attr {
-    key: "T"
-    value { type: DT_FLOAT }
-  }
-  attr {
-    key: "Tshape"
-    value { type: DT_INT32 }
-  }
-}
-node {
-  name: "softmax"
-  op: "Softmax"
-  input: "reshape_1"
-  attr {
-    key: "T"
-    value { type: DT_FLOAT }
-  }
-}
-node {
-  name: "shape"
-  op: "Shape"
-  input: "squeeze"
-  attr {
-    key: "T"
-    value { type: DT_FLOAT }
-  }
-  attr {
-    key: "out_type"
-    value { type: DT_INT32 }
-  }
-}
-node {
-  name: "reshape_2"
-  op: "Reshape"
-  input: "softmax"
-  input: "shape"
-  attr {
-    key: "T"
-    value { type: DT_FLOAT }
-  }
-  attr {
-    key: "Tshape"
-    value { type: DT_INT32 }
-  }
-}
diff --git a/res/TensorFlowTests/TF_IV3_MaxPool/test.info b/res/TensorFlowTests/TF_IV3_MaxPool/test.info
deleted file mode 100644
index 059b21c..0000000
--- a/res/TensorFlowTests/TF_IV3_MaxPool/test.info
+++ /dev/null
@@ -1,2 +0,0 @@
-input,  placeholder:0,  TF_FLOAT,   [1, 7, 7, 1]
-output, maxpool2d:0,    TF_FLOAT,   [1, 3, 3, 1]
diff --git a/res/TensorFlowTests/TF_IV3_MaxPool/test.pbtxt b/res/TensorFlowTests/TF_IV3_MaxPool/test.pbtxt
deleted file mode 100644
index b1eadcc..0000000
--- a/res/TensorFlowTests/TF_IV3_MaxPool/test.pbtxt
+++ /dev/null
@@ -1,65 +0,0 @@
-# HOW TO GENERATE:
-#
-#  import tensorflow as tf
-#  value = tf.placeholder(dtype=tf.float32, shape=[1, 7, 7, 1], name='placeholder')
-#  output = tf.nn.max_pool(value, [1, 3, 3, 1], [1, 2, 2, 1], 'VALID', name='maxpool2d')
-#  tf.get_default_graph().as_graph_def()
-#
-# NOTE 1. The output shape is 1x3x3x1
-#
-# >>> tf.graph_util.tensor_shape_from_node_def_name(tf.get_default_graph(), 'maxpool2d')
-# TensorShape([Dimension(1), Dimension(3), Dimension(3), Dimension(1)])
-#
-# NOTE 2. All the MaxPool nodes in inception v3 2018.04.27 use this configuration.
-# - InceptionV3/InceptionV3/MaxPool_3a_3x3/MaxPool
-# - InceptionV3/InceptionV3/MaxPool_5a_3x3/MaxPool
-# - InceptionV3/InceptionV3/Mixed_6a/Branch_2/MaxPool_1a_3x3/MaxPool
-# - InceptionV3/InceptionV3/Mixed_7a/Branch_2/MaxPool_1a_3x3/MaxPool
-node {
-  name: "placeholder"
-  op: "Placeholder"
-  attr {
-    key: "dtype"
-    value { type: DT_FLOAT }
-  }
-  attr {
-    key: "shape"
-    value {
-      shape {
-        dim { size: 1 }
-        dim { size: 7 }
-        dim { size: 7 }
-        dim { size: 1 }
-      }
-    }
-  }
-}
-node {
-  name: "maxpool2d"
-  op: "MaxPool"
-  input: "placeholder"
-  attr {
-    key: "T"
-    value { type: DT_FLOAT }
-  }
-  attr {
-    key: "data_format"
-    value { s: "NHWC" }
-  }
-  attr {
-    key: "ksize"
-    value {
-      list { i: 1 i: 3 i: 3 i: 1 }
-    }
-  }
-  attr {
-    key: "padding"
-    value { s: "VALID" }
-  }
-  attr {
-    key: "strides"
-    value {
-      list { i: 1 i: 2 i: 2 i: 1 }
-    }
-  }
-}