From e6546baa6283bbfddc9e925382dc754954eb3bf8 Mon Sep 17 00:00:00 2001
From: dzhwinter <dongzhihong01@baidu.com>
Date: Mon, 27 Nov 2017 13:09:23 +0800
Subject: [PATCH] remove unused file (#5918)

---
 .../fluid/tests/tmp/inference_model/__model__ | Bin 1255 -> 0 bytes
 .../fluid/tests/tmp/inference_model/fc_0.b_0  | Bin 24 -> 0 bytes
 .../fluid/tests/tmp/inference_model/fc_0.w_0  | Bin 30 -> 0 bytes
 .../tests/test_elementwise_mod_op.py          |  36 ------------------
 4 files changed, 36 deletions(-)
 delete mode 100644 python/paddle/v2/fluid/tests/tmp/inference_model/__model__
 delete mode 100644 python/paddle/v2/fluid/tests/tmp/inference_model/fc_0.b_0
 delete mode 100644 python/paddle/v2/fluid/tests/tmp/inference_model/fc_0.w_0
 delete mode 100644 python/paddle/v2/framework/tests/test_elementwise_mod_op.py

diff --git a/python/paddle/v2/fluid/tests/tmp/inference_model/__model__ b/python/paddle/v2/fluid/tests/tmp/inference_model/__model__
deleted file mode 100644
index e333d10da94943372b0fe4dedd9d857817ec9ca6..0000000000000000000000000000000000000000
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diff --git a/python/paddle/v2/fluid/tests/tmp/inference_model/fc_0.b_0 b/python/paddle/v2/fluid/tests/tmp/inference_model/fc_0.b_0
deleted file mode 100644
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diff --git a/python/paddle/v2/fluid/tests/tmp/inference_model/fc_0.w_0 b/python/paddle/v2/fluid/tests/tmp/inference_model/fc_0.w_0
deleted file mode 100644
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diff --git a/python/paddle/v2/framework/tests/test_elementwise_mod_op.py b/python/paddle/v2/framework/tests/test_elementwise_mod_op.py
deleted file mode 100644
index 35c38147a24..00000000000
--- a/python/paddle/v2/framework/tests/test_elementwise_mod_op.py
+++ /dev/null
@@ -1,36 +0,0 @@
-import unittest
-import numpy as np
-from op_test import OpTest
-
-
-class ElementwiseModOp(OpTest):
-    def setUp(self):
-        self.op_type = "elementwise_mod"
-        """ Warning
-        CPU gradient check error!
-        'X': np.random.randint((32,84)).astype("int32"),
-        'Y': np.random.randint((32,84)).astype("int32")
-        """
-        self.inputs = {
-            'X': np.random.randint(1, 10, [13, 17]).astype("int32"),
-            'Y': np.random.randint(1, 10, [13, 17]).astype("int32")
-        }
-        self.outputs = {'Out': np.mod(self.inputs['X'], self.inputs['Y'])}
-
-    def test_check_output(self):
-        self.check_output()
-
-    def test_check_grad_normal(self):
-        self.check_grad(['X', 'Y'], 'Out', max_relative_error=0.05)
-
-    def test_check_grad_ingore_x(self):
-        self.check_grad(
-            ['Y'], 'Out', max_relative_error=0.05, no_grad_set=set("X"))
-
-    def test_check_grad_ingore_y(self):
-        self.check_grad(
-            ['X'], 'Out', max_relative_error=0.05, no_grad_set=set('Y'))
-
-
-if __name__ == '__main__':
-    unittest.main()
-- 
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