Clean up tf.print tests
- Remove with cached_session blocks - Use run_all_in_graph_and_eager_modes on entire class - Use assertIn instead of assertTrue PiperOrigin-RevId: 292730904 Change-Id: Iabc6e321a02cda4e9b2b6604c717a6d9a129d2a0
This commit is contained in:
Gaurav Jain
TensorFlower Gardener
parent
adf769043f
commit
0aba717531
@ -69,244 +69,209 @@ class LoggingOpsTest(test.TestCase):
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self.evaluate(out)
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@test_util.run_all_in_graph_and_eager_modes
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class PrintV2Test(test.TestCase):
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@test_util.run_in_graph_and_eager_modes()
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def testPrintOneTensor(self):
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with self.cached_session():
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor)
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self.evaluate(print_op)
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor)
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self.evaluate(print_op)
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expected = "[0 1 2 ... 7 8 9]"
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self.assertTrue((expected + "\n") in printed.contents())
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expected = "[0 1 2 ... 7 8 9]"
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self.assertIn((expected + "\n"), printed.contents())
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@test_util.run_in_graph_and_eager_modes()
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def testPrintOneStringTensor(self):
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with self.cached_session():
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tensor = ops.convert_to_tensor([char for char in string.ascii_lowercase])
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor)
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self.evaluate(print_op)
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tensor = ops.convert_to_tensor([char for char in string.ascii_lowercase])
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor)
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self.evaluate(print_op)
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expected = "[\"a\" \"b\" \"c\" ... \"x\" \"y\" \"z\"]"
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self.assertIn((expected + "\n"), printed.contents())
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expected = "[\"a\" \"b\" \"c\" ... \"x\" \"y\" \"z\"]"
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self.assertIn((expected + "\n"), printed.contents())
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@test_util.run_in_graph_and_eager_modes()
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def testPrintOneTensorVarySummarize(self):
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with self.cached_session():
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor, summarize=1)
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self.evaluate(print_op)
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor, summarize=1)
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self.evaluate(print_op)
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expected = "[0 ... 9]"
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self.assertTrue((expected + "\n") in printed.contents())
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expected = "[0 ... 9]"
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self.assertIn((expected + "\n"), printed.contents())
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with self.cached_session():
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor, summarize=2)
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self.evaluate(print_op)
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor, summarize=2)
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self.evaluate(print_op)
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expected = "[0 1 ... 8 9]"
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self.assertTrue((expected + "\n") in printed.contents())
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expected = "[0 1 ... 8 9]"
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self.assertIn((expected + "\n"), printed.contents())
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with self.cached_session():
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor, summarize=3)
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self.evaluate(print_op)
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor, summarize=3)
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self.evaluate(print_op)
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expected = "[0 1 2 ... 7 8 9]"
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self.assertTrue((expected + "\n") in printed.contents())
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expected = "[0 1 2 ... 7 8 9]"
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self.assertIn((expected + "\n"), printed.contents())
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with self.cached_session():
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor, summarize=-1)
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self.evaluate(print_op)
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor, summarize=-1)
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self.evaluate(print_op)
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expected = "[0 1 2 3 4 5 6 7 8 9]"
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self.assertTrue((expected + "\n") in printed.contents())
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expected = "[0 1 2 3 4 5 6 7 8 9]"
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self.assertIn((expected + "\n"), printed.contents())
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@test_util.run_in_graph_and_eager_modes()
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def testPrintOneVariable(self):
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with self.cached_session():
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var = variables.Variable(math_ops.range(10))
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if not context.executing_eagerly():
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variables.global_variables_initializer().run()
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(var)
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self.evaluate(print_op)
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expected = "[0 1 2 ... 7 8 9]"
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self.assertTrue((expected + "\n") in printed.contents())
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var = variables.Variable(math_ops.range(10))
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if not context.executing_eagerly():
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variables.global_variables_initializer().run()
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(var)
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self.evaluate(print_op)
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expected = "[0 1 2 ... 7 8 9]"
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self.assertIn((expected + "\n"), printed.contents())
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@test_util.run_in_graph_and_eager_modes()
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def testPrintTwoVariablesInStructWithAssignAdd(self):
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with self.cached_session():
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var_one = variables.Variable(2.14)
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plus_one = var_one.assign_add(1.0)
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var_two = variables.Variable(math_ops.range(10))
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if not context.executing_eagerly():
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variables.global_variables_initializer().run()
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with self.captureWritesToStream(sys.stderr) as printed:
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self.evaluate(plus_one)
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print_op = logging_ops.print_v2(var_one, {"second": var_two})
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self.evaluate(print_op)
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expected = "3.14 {'second': [0 1 2 ... 7 8 9]}"
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self.assertTrue((expected + "\n") in printed.contents())
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var_one = variables.Variable(2.14)
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plus_one = var_one.assign_add(1.0)
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var_two = variables.Variable(math_ops.range(10))
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if not context.executing_eagerly():
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variables.global_variables_initializer().run()
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with self.captureWritesToStream(sys.stderr) as printed:
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self.evaluate(plus_one)
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print_op = logging_ops.print_v2(var_one, {"second": var_two})
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self.evaluate(print_op)
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expected = "3.14 {'second': [0 1 2 ... 7 8 9]}"
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self.assertIn((expected + "\n"), printed.contents())
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@test_util.run_in_graph_and_eager_modes()
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def testPrintTwoTensors(self):
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with self.cached_session():
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor, tensor * 10)
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self.evaluate(print_op)
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expected = "[0 1 2 ... 7 8 9] [0 10 20 ... 70 80 90]"
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self.assertTrue((expected + "\n") in printed.contents())
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor, tensor * 10)
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self.evaluate(print_op)
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expected = "[0 1 2 ... 7 8 9] [0 10 20 ... 70 80 90]"
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self.assertIn((expected + "\n"), printed.contents())
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@test_util.run_in_graph_and_eager_modes()
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def testPrintTwoTensorsDifferentSep(self):
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with self.cached_session():
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor, tensor * 10, sep="<separator>")
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self.evaluate(print_op)
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expected = "[0 1 2 ... 7 8 9]<separator>[0 10 20 ... 70 80 90]"
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self.assertIn(expected + "\n", printed.contents())
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor, tensor * 10, sep="<separator>")
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self.evaluate(print_op)
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expected = "[0 1 2 ... 7 8 9]<separator>[0 10 20 ... 70 80 90]"
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self.assertIn(expected + "\n", printed.contents())
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@test_util.run_in_graph_and_eager_modes()
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def testPrintPlaceholderGeneration(self):
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with self.cached_session():
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2("{}6", {"{}": tensor * 10})
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self.evaluate(print_op)
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expected = "{}6 {'{}': [0 10 20 ... 70 80 90]}"
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self.assertTrue((expected + "\n") in printed.contents())
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2("{}6", {"{}": tensor * 10})
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self.evaluate(print_op)
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expected = "{}6 {'{}': [0 10 20 ... 70 80 90]}"
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self.assertIn((expected + "\n"), printed.contents())
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@test_util.run_in_graph_and_eager_modes()
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def testPrintNoTensors(self):
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with self.cached_session():
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(23, [23, 5], {"6": 12})
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self.evaluate(print_op)
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expected = "23 [23, 5] {'6': 12}"
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self.assertTrue((expected + "\n") in printed.contents())
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(23, [23, 5], {"6": 12})
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self.evaluate(print_op)
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expected = "23 [23, 5] {'6': 12}"
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self.assertIn((expected + "\n"), printed.contents())
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@test_util.run_in_graph_and_eager_modes()
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def testPrintFloatScalar(self):
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with self.cached_session():
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tensor = ops.convert_to_tensor(434.43)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor)
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self.evaluate(print_op)
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expected = "434.43"
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self.assertTrue((expected + "\n") in printed.contents())
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tensor = ops.convert_to_tensor(434.43)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor)
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self.evaluate(print_op)
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expected = "434.43"
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self.assertIn((expected + "\n"), printed.contents())
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@test_util.run_in_graph_and_eager_modes()
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def testPrintStringScalar(self):
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with self.cached_session():
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tensor = ops.convert_to_tensor("scalar")
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor)
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self.evaluate(print_op)
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expected = "scalar"
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self.assertTrue((expected + "\n") in printed.contents())
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tensor = ops.convert_to_tensor("scalar")
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor)
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self.evaluate(print_op)
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expected = "scalar"
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self.assertIn((expected + "\n"), printed.contents())
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@test_util.run_in_graph_and_eager_modes()
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def testPrintStringScalarDifferentEnd(self):
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with self.cached_session():
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tensor = ops.convert_to_tensor("scalar")
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor, end="<customend>")
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self.evaluate(print_op)
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expected = "scalar<customend>"
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self.assertIn(expected, printed.contents())
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tensor = ops.convert_to_tensor("scalar")
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(tensor, end="<customend>")
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self.evaluate(print_op)
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expected = "scalar<customend>"
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self.assertIn(expected, printed.contents())
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@test_util.run_in_graph_and_eager_modes()
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def testPrintComplexTensorStruct(self):
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with self.cached_session():
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tensor = math_ops.range(10)
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small_tensor = constant_op.constant([0.3, 12.4, -16.1])
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big_tensor = math_ops.mul(tensor, 10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(
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"first:", tensor, "middle:",
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{"small": small_tensor, "Big": big_tensor}, 10,
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[tensor * 2, tensor])
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self.evaluate(print_op)
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# Note that the keys in the dict will always be sorted,
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# so 'Big' comes before 'small'
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expected = ("first: [0 1 2 ... 7 8 9] "
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"middle: {'Big': [0 10 20 ... 70 80 90], "
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"'small': [0.3 12.4 -16.1]} "
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"10 [[0 2 4 ... 14 16 18], [0 1 2 ... 7 8 9]]")
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self.assertTrue((expected + "\n") in printed.contents())
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tensor = math_ops.range(10)
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small_tensor = constant_op.constant([0.3, 12.4, -16.1])
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big_tensor = math_ops.mul(tensor, 10)
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(
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"first:", tensor, "middle:",
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{"small": small_tensor, "Big": big_tensor}, 10,
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[tensor * 2, tensor])
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self.evaluate(print_op)
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# Note that the keys in the dict will always be sorted,
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# so 'Big' comes before 'small'
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expected = ("first: [0 1 2 ... 7 8 9] "
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"middle: {'Big': [0 10 20 ... 70 80 90], "
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"'small': [0.3 12.4 -16.1]} "
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"10 [[0 2 4 ... 14 16 18], [0 1 2 ... 7 8 9]]")
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self.assertIn((expected + "\n"), printed.contents())
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@test_util.run_in_graph_and_eager_modes()
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def testPrintSparseTensor(self):
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with self.cached_session():
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ind = [[0, 0], [1, 0], [1, 3], [4, 1], [1, 4], [3, 2], [3, 3]]
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val = [0, 10, 13, 4, 14, 32, 33]
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shape = [5, 6]
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ind = [[0, 0], [1, 0], [1, 3], [4, 1], [1, 4], [3, 2], [3, 3]]
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val = [0, 10, 13, 4, 14, 32, 33]
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shape = [5, 6]
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sparse = sparse_tensor.SparseTensor(
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constant_op.constant(ind, dtypes.int64),
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constant_op.constant(val, dtypes.int64),
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constant_op.constant(shape, dtypes.int64))
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sparse = sparse_tensor.SparseTensor(
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constant_op.constant(ind, dtypes.int64),
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constant_op.constant(val, dtypes.int64),
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constant_op.constant(shape, dtypes.int64))
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(sparse)
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self.evaluate(print_op)
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expected = ("'SparseTensor(indices=[[0 0]\n"
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" [1 0]\n"
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" [1 3]\n"
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" ...\n"
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" [1 4]\n"
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" [3 2]\n"
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" [3 3]], values=[0 10 13 ... 14 32 33], shape=[5 6])'")
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self.assertTrue((expected + "\n") in printed.contents())
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2(sparse)
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self.evaluate(print_op)
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expected = ("'SparseTensor(indices=[[0 0]\n"
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" [1 0]\n"
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" [1 3]\n"
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" ...\n"
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" [1 4]\n"
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" [3 2]\n"
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" [3 3]], values=[0 10 13 ... 14 32 33], shape=[5 6])'")
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self.assertIn((expected + "\n"), printed.contents())
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@test_util.run_in_graph_and_eager_modes()
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def testPrintSparseTensorInDataStruct(self):
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with self.cached_session():
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ind = [[0, 0], [1, 0], [1, 3], [4, 1], [1, 4], [3, 2], [3, 3]]
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val = [0, 10, 13, 4, 14, 32, 33]
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shape = [5, 6]
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ind = [[0, 0], [1, 0], [1, 3], [4, 1], [1, 4], [3, 2], [3, 3]]
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val = [0, 10, 13, 4, 14, 32, 33]
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shape = [5, 6]
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sparse = sparse_tensor.SparseTensor(
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constant_op.constant(ind, dtypes.int64),
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constant_op.constant(val, dtypes.int64),
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constant_op.constant(shape, dtypes.int64))
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sparse = sparse_tensor.SparseTensor(
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constant_op.constant(ind, dtypes.int64),
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constant_op.constant(val, dtypes.int64),
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constant_op.constant(shape, dtypes.int64))
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2([sparse])
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self.evaluate(print_op)
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expected = ("['SparseTensor(indices=[[0 0]\n"
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" [1 0]\n"
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" [1 3]\n"
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" ...\n"
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" [1 4]\n"
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" [3 2]\n"
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" [3 3]], values=[0 10 13 ... 14 32 33], shape=[5 6])']")
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self.assertTrue((expected + "\n") in printed.contents())
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with self.captureWritesToStream(sys.stderr) as printed:
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print_op = logging_ops.print_v2([sparse])
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self.evaluate(print_op)
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expected = ("['SparseTensor(indices=[[0 0]\n"
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" [1 0]\n"
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" [1 3]\n"
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" ...\n"
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" [1 4]\n"
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" [3 2]\n"
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" [3 3]], values=[0 10 13 ... 14 32 33], shape=[5 6])']")
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self.assertIn((expected + "\n"), printed.contents())
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@test_util.run_in_graph_and_eager_modes()
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def testPrintOneTensorStdout(self):
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with self.cached_session():
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stdout) as printed:
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print_op = logging_ops.print_v2(
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tensor, output_stream=sys.stdout)
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self.evaluate(print_op)
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expected = "[0 1 2 ... 7 8 9]"
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self.assertTrue((expected + "\n") in printed.contents())
|
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tensor = math_ops.range(10)
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with self.captureWritesToStream(sys.stdout) as printed:
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print_op = logging_ops.print_v2(
|
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tensor, output_stream=sys.stdout)
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self.evaluate(print_op)
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expected = "[0 1 2 ... 7 8 9]"
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self.assertIn((expected + "\n"), printed.contents())
|
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|
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@test_util.run_in_graph_and_eager_modes()
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def testPrintTensorsToFile(self):
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tmpfile_name = tempfile.mktemp(".printv2_test")
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tensor_0 = math_ops.range(0, 10)
|
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@ -330,42 +295,37 @@ class PrintV2Test(test.TestCase):
|
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except IOError as e:
|
||||
self.fail(e)
|
||||
|
||||
@test_util.run_in_graph_and_eager_modes()
|
||||
def testInvalidOutputStreamRaisesError(self):
|
||||
with self.cached_session():
|
||||
tensor = math_ops.range(10)
|
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with self.assertRaises(ValueError):
|
||||
print_op = logging_ops.print_v2(
|
||||
tensor, output_stream="unknown")
|
||||
self.evaluate(print_op)
|
||||
tensor = math_ops.range(10)
|
||||
with self.assertRaises(ValueError):
|
||||
print_op = logging_ops.print_v2(
|
||||
tensor, output_stream="unknown")
|
||||
self.evaluate(print_op)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
def testPrintOpName(self):
|
||||
with self.cached_session():
|
||||
tensor = math_ops.range(10)
|
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print_op = logging_ops.print_v2(tensor, name="print_name")
|
||||
self.assertEqual(print_op.name, "print_name")
|
||||
tensor = math_ops.range(10)
|
||||
print_op = logging_ops.print_v2(tensor, name="print_name")
|
||||
self.assertEqual(print_op.name, "print_name")
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
def testNoDuplicateFormatOpGraphModeAfterExplicitFormat(self):
|
||||
with self.cached_session():
|
||||
tensor = math_ops.range(10)
|
||||
formatted_string = string_ops.string_format("{}", tensor)
|
||||
print_op = logging_ops.print_v2(formatted_string)
|
||||
self.evaluate(print_op)
|
||||
graph_ops = ops.get_default_graph().get_operations()
|
||||
format_ops = [op for op in graph_ops if op.type == "StringFormat"]
|
||||
# Should be only 1 format_op for graph mode.
|
||||
self.assertEqual(len(format_ops), 1)
|
||||
tensor = math_ops.range(10)
|
||||
formatted_string = string_ops.string_format("{}", tensor)
|
||||
print_op = logging_ops.print_v2(formatted_string)
|
||||
self.evaluate(print_op)
|
||||
graph_ops = ops.get_default_graph().get_operations()
|
||||
format_ops = [op for op in graph_ops if op.type == "StringFormat"]
|
||||
# Should be only 1 format_op for graph mode.
|
||||
self.assertEqual(len(format_ops), 1)
|
||||
|
||||
def testPrintOneTensorEagerOnOpCreate(self):
|
||||
with self.cached_session():
|
||||
with context.eager_mode():
|
||||
tensor = math_ops.range(10)
|
||||
expected = "[0 1 2 ... 7 8 9]"
|
||||
with self.captureWritesToStream(sys.stderr) as printed:
|
||||
logging_ops.print_v2(tensor)
|
||||
self.assertTrue((expected + "\n") in printed.contents())
|
||||
with context.eager_mode():
|
||||
tensor = math_ops.range(10)
|
||||
expected = "[0 1 2 ... 7 8 9]"
|
||||
with self.captureWritesToStream(sys.stderr) as printed:
|
||||
logging_ops.print_v2(tensor)
|
||||
self.assertIn((expected + "\n"), printed.contents())
|
||||
|
||||
def testPrintsOrderedInDefun(self):
|
||||
with context.eager_mode():
|
||||
@ -378,9 +338,8 @@ class PrintV2Test(test.TestCase):
|
||||
|
||||
with self.captureWritesToStream(sys.stderr) as printed:
|
||||
prints()
|
||||
self.assertTrue(("A\nB\nC\n") in printed.contents())
|
||||
self.assertTrue(("A\nB\nC\n"), printed.contents())
|
||||
|
||||
@test_util.run_in_graph_and_eager_modes()
|
||||
def testPrintInDefunWithoutExplicitEvalOfPrint(self):
|
||||
@function.defun
|
||||
def f():
|
||||
@ -392,14 +351,14 @@ class PrintV2Test(test.TestCase):
|
||||
with self.captureWritesToStream(sys.stderr) as printed_one:
|
||||
x = f()
|
||||
self.evaluate(x)
|
||||
self.assertTrue((expected + "\n") in printed_one.contents())
|
||||
self.assertIn((expected + "\n"), printed_one.contents())
|
||||
|
||||
# We execute the function again to make sure it doesn't only print on the
|
||||
# first call.
|
||||
with self.captureWritesToStream(sys.stderr) as printed_two:
|
||||
y = f()
|
||||
self.evaluate(y)
|
||||
self.assertTrue((expected + "\n") in printed_two.contents())
|
||||
self.assertIn((expected + "\n"), printed_two.contents())
|
||||
|
||||
|
||||
class PrintGradientTest(test.TestCase):
|
||||
@ -417,15 +376,14 @@ class PrintGradientTest(test.TestCase):
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
def testPrintGradient(self):
|
||||
with self.cached_session():
|
||||
inp = constant_op.constant(2.0, shape=[100, 32], name="in")
|
||||
w = constant_op.constant(4.0, shape=[10, 100], name="w")
|
||||
wx = math_ops.matmul(w, inp, name="wx")
|
||||
wx_print = logging_ops.Print(wx, [w, w, w])
|
||||
wx_grad = gradients_impl.gradients(wx, w)[0]
|
||||
wx_print_grad = gradients_impl.gradients(wx_print, w)[0]
|
||||
wxg = self.evaluate(wx_grad)
|
||||
wxpg = self.evaluate(wx_print_grad)
|
||||
inp = constant_op.constant(2.0, shape=[100, 32], name="in")
|
||||
w = constant_op.constant(4.0, shape=[10, 100], name="w")
|
||||
wx = math_ops.matmul(w, inp, name="wx")
|
||||
wx_print = logging_ops.Print(wx, [w, w, w])
|
||||
wx_grad = gradients_impl.gradients(wx, w)[0]
|
||||
wx_print_grad = gradients_impl.gradients(wx_print, w)[0]
|
||||
wxg = self.evaluate(wx_grad)
|
||||
wxpg = self.evaluate(wx_print_grad)
|
||||
self.assertAllEqual(wxg, wxpg)
|
||||
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user