{"action":"created","issue":{"url":"https://api.github.com/repos/tensorflow/tensorflow/issues/5300","repository_url":"https://api.github.com/repos/tensorflow/tensorflow","labels_url":"https://api.github.com/repos/tensorflow/tensorflow/issues/5300/labels{/name}","comments_url":"https://api.github.com/repos/tensorflow/tensorflow/issues/5300/comments","events_url":"https://api.github.com/repos/tensorflow/tensorflow/issues/5300/events","html_url":"https://github.com/tensorflow/tensorflow/pull/5300","id":186240624,"number":5300,"title":"Add atrous_conv2d_transpose python 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description : https://github.com/tensorflow/tensorflow/issues/4668\r\n\r\nThis is the first commit of the issue.\r\nI will commit the unit test later.\r\nI will also add the comment for the method.\r\n\r\n**Thank you for any advice.**\r\n\r\nNow I test it with:\r\n\r\n```\r\n\r\n# Input, output: [batch, height, width, depth]\r\nx_image = tf.placeholder(tf.float32,shape=[1])\r\nx = tf.reshape(x_image,[1,1,1,1])\r\n\r\n#Filter: W [kernel_height, kernel_width, output_depth, input_depth]\r\nW_cpu = np.array([[1,-1,1],[1,1,1],[-1,1,-1]],dtype=np.float32)\r\nW = tf.Variable(W_cpu)\r\nW = tf.reshape(W, [3,3,1,1])\r\n\r\nstrides=[1, 1, 1, 1]\r\npadding='VALID'\r\n\r\ny = tf.nn.atrous_conv2d_transpose(x, W, [1,5,5,1], 2, strides, padding)\r\n\r\nx_data = np.array([1],dtype=np.float32)\r\nwith tf.Session() as sess:\r\n    init = tf.initialize_all_variables()\r\n    sess.run(init)\r\n\r\n    x = (sess.run(x, feed_dict={x_image: x_data}))\r\n    W = (sess.run(W, feed_dict={x_image: x_data}))\r\n    y = (sess.run(y, feed_dict={x_image: x_data}))\r\n\r\n    print \"The shape of x:\\t\", x.shape, \",\\t and the x.reshape(1) is :\"\r\n    print x.reshape(1)\r\n    print \"\"\r\n\r\n    print \"The shape of x:\\t\", W.shape, \",\\t and the W.reshape(3,3) is :\"\r\n    print W.reshape(3,3)\r\n    print \"\"\r\n\r\n    print \"The shape of y:\\t\", y.shape, \",\\t and the y.reshape(5,5) is :\"\r\n    print y.reshape(5,5)\r\n    print \"\"\r\n```\r\n\r\nand \r\n\r\n```\r\n  def testAtrousConv2DTransposeSingleStride(self):\r\n    with self.test_session():\r\n      strides = [1, 1, 1, 1]\r\n\r\n      # Input, output: [batch, height, width, depth]\r\n      x_shape = [2, 6, 4, 3]\r\n      y_shape = [2, 6, 4, 2]\r\n\r\n      # Filter: [kernel_height, kernel_width, output_depth, input_depth]\r\n      f_shape = [3, 3, 2, 3]\r\n\r\n      x = tf.constant(1.0, shape=x_shape, name=\"x\", dtype=tf.float32)\r\n      f = tf.constant(1.0, shape=f_shape, name=\"filter\", dtype=tf.float32)\r\n\r\n      output = tf.nn.atrous_conv2d_transpose(x, f, y_shape, 2, strides=strides,\r\n                                      padding=\"SAME\")\r\n\r\n      value = output.eval()\r\n      print(value)\r\n```"},"comment":{"url":"https://api.github.com/repos/tensorflow/tensorflow/issues/comments/263765542","html_url":"https://github.com/tensorflow/tensorflow/pull/5300#issuecomment-263765542","issue_url":"https://api.github.com/repos/tensorflow/tensorflow/issues/5300","id":263765542,"user":{"login":"guotong1988","id":4702353,"avatar_url":"https://avatars.githubusercontent.com/u/4702353?v=3","gravatar_id":"","url":"https://api.github.com/users/guotong1988","html_url":"https://github.com/guotong1988","followers_url":"https://api.github.com/users/guotong1988/followers","following_url":"https://api.github.com/users/guotong1988/following{/other_user}","gists_url":"https://api.github.com/users/guotong1988/gists{/gist_id}","starred_url":"https://api.github.com/users/guotong1988/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/guotong1988/subscriptions","organizations_url":"https://api.github.com/users/guotong1988/orgs","repos_url":"https://api.github.com/users/guotong1988/repos","events_url":"https://api.github.com/users/guotong1988/events{/privacy}","received_events_url":"https://api.github.com/users/guotong1988/received_events","type":"User","site_admin":false},"created_at":"2016-11-30T02:33:55Z","updated_at":"2016-11-30T02:33:55Z","body":" @sbrodehl In fact I'm not sure that my only test case can cover that much . Please provide more test case, if you have. Thank you ."}}
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