44113ce5bb
RELNOTES: TensorFlow Debugger (tfdbg) command-line interface: Support evaluation of arbitrary Python and numpy (np) expressions with debug tensor names enclosed in pairs of backtics. E.g., tfdbg> eval 'np.sum(`Softmax:0`, axis=1)'. PiperOrigin-RevId: 164217384
269 lines
11 KiB
Python
269 lines
11 KiB
Python
# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Tests for arbitrary expression evaluator."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import numpy as np
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from tensorflow.python.debug.cli import evaluator
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from tensorflow.python.debug.lib import debug_data
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from tensorflow.python.framework import test_util
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from tensorflow.python.platform import test
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class ParseDebugTensorNameTest(test_util.TensorFlowTestCase):
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def testParseNamesWithoutPrefixOrSuffix(self):
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device_name, node_name, output_slot, debug_op, exec_index = (
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evaluator._parse_debug_tensor_name("foo:1"))
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self.assertIsNone(device_name)
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self.assertEqual("foo", node_name)
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self.assertEqual(1, output_slot)
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self.assertEqual("DebugIdentity", debug_op)
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self.assertEqual(0, exec_index)
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device_name, node_name, output_slot, debug_op, exec_index = (
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evaluator._parse_debug_tensor_name("hidden_0/Weights:0"))
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self.assertIsNone(device_name)
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self.assertEqual("hidden_0/Weights", node_name)
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self.assertEqual(0, output_slot)
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self.assertEqual("DebugIdentity", debug_op)
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self.assertEqual(0, exec_index)
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def testParseNamesWithoutPrefixWithDebugOpSuffix(self):
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device_name, node_name, output_slot, debug_op, exec_index = (
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evaluator._parse_debug_tensor_name("foo:1:DebugNanCount"))
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self.assertIsNone(device_name)
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self.assertEqual("foo", node_name)
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self.assertEqual(1, output_slot)
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self.assertEqual("DebugNanCount", debug_op)
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self.assertEqual(0, exec_index)
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device_name, node_name, output_slot, debug_op, exec_index = (
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evaluator._parse_debug_tensor_name(
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"hidden_0/Weights:0:DebugNumericSummary"))
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self.assertIsNone(device_name)
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self.assertEqual("hidden_0/Weights", node_name)
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self.assertEqual(0, output_slot)
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self.assertEqual("DebugNumericSummary", debug_op)
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self.assertEqual(0, exec_index)
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def testParseNamesWithDeviceNamePrefixWithoutDebugOpSuffix(self):
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device_name, node_name, output_slot, debug_op, exec_index = (
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evaluator._parse_debug_tensor_name(
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"/job:ps/replica:0/task:2/cpu:0:foo:1"))
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self.assertEqual("/job:ps/replica:0/task:2/cpu:0", device_name)
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self.assertEqual("foo", node_name)
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self.assertEqual(1, output_slot)
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self.assertEqual("DebugIdentity", debug_op)
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self.assertEqual(0, exec_index)
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device_name, node_name, output_slot, debug_op, exec_index = (
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evaluator._parse_debug_tensor_name(
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"/job:worker/replica:0/task:3/gpu:0:hidden_0/Weights:0"))
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self.assertEqual("/job:worker/replica:0/task:3/gpu:0", device_name)
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self.assertEqual("hidden_0/Weights", node_name)
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self.assertEqual(0, output_slot)
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self.assertEqual("DebugIdentity", debug_op)
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self.assertEqual(0, exec_index)
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def testParseNamesWithDeviceNamePrefixWithDebugOpSuffix(self):
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device_name, node_name, output_slot, debug_op, exec_index = (
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evaluator._parse_debug_tensor_name(
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"/job:ps/replica:0/task:2/cpu:0:foo:1:DebugNanCount"))
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self.assertEqual("/job:ps/replica:0/task:2/cpu:0", device_name)
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self.assertEqual("foo", node_name)
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self.assertEqual(1, output_slot)
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self.assertEqual("DebugNanCount", debug_op)
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self.assertEqual(0, exec_index)
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device_name, node_name, output_slot, debug_op, exec_index = (
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evaluator._parse_debug_tensor_name(
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"/job:worker/replica:0/task:3/gpu:0:"
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"hidden_0/Weights:0:DebugNumericSummary"))
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self.assertEqual("/job:worker/replica:0/task:3/gpu:0", device_name)
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self.assertEqual("hidden_0/Weights", node_name)
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self.assertEqual(0, output_slot)
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self.assertEqual("DebugNumericSummary", debug_op)
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self.assertEqual(0, exec_index)
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def testParseMalformedDebugTensorName(self):
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with self.assertRaisesRegexp(
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ValueError,
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r"The debug tensor name in the to-be-evaluated expression is "
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r"malformed:"):
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evaluator._parse_debug_tensor_name(
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"/job:ps/replica:0/task:2/cpu:0:foo:1:DebugNanCount:1337")
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with self.assertRaisesRegexp(
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ValueError,
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r"The debug tensor name in the to-be-evaluated expression is "
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r"malformed:"):
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evaluator._parse_debug_tensor_name(
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"/job:ps/replica:0/cpu:0:foo:1:DebugNanCount")
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with self.assertRaises(ValueError):
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evaluator._parse_debug_tensor_name(
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"foo:1:DebugNanCount[]")
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with self.assertRaises(ValueError):
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evaluator._parse_debug_tensor_name(
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"foo:1[DebugNanCount]")
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def testParseNamesWithExecIndex(self):
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device_name, node_name, output_slot, debug_op, exec_index = (
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evaluator._parse_debug_tensor_name("foo:1[20]"))
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self.assertIsNone(device_name)
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self.assertEqual("foo", node_name)
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self.assertEqual(1, output_slot)
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self.assertEqual("DebugIdentity", debug_op)
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self.assertEqual(20, exec_index)
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device_name, node_name, output_slot, debug_op, exec_index = (
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evaluator._parse_debug_tensor_name("hidden_0/Weights:0[3]"))
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self.assertIsNone(device_name)
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self.assertEqual("hidden_0/Weights", node_name)
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self.assertEqual(0, output_slot)
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self.assertEqual("DebugIdentity", debug_op)
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self.assertEqual(3, exec_index)
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class EvaluatorTest(test_util.TensorFlowTestCase):
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def testEvaluateSingleTensor(self):
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dump = test.mock.MagicMock()
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def fake_get_tensors(node_name, output_slot, debug_op, device_name=None):
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del node_name, output_slot, debug_op, device_name # Unused.
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return [np.array([[1.0, 2.0, 3.0]])]
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with test.mock.patch.object(
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dump, "get_tensors", side_effect=fake_get_tensors, autospec=True):
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ev = evaluator.ExpressionEvaluator(dump)
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self.assertEqual(3, ev.evaluate("np.size(`a:0`)"))
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# Whitespace in backticks should be tolerated.
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self.assertEqual(3, ev.evaluate("np.size(` a:0 `)"))
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def testEvaluateTwoTensors(self):
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dump = test.mock.MagicMock()
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def fake_get_tensors(node_name, output_slot, debug_op, device_name=None):
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del debug_op, device_name # Unused.
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if node_name == "a" and output_slot == 0:
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return [np.array([[1.0, -2.0], [0.0, 1.0]])]
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elif node_name == "b" and output_slot == 0:
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return [np.array([[-1.0], [1.0]])]
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with test.mock.patch.object(
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dump, "get_tensors", side_effect=fake_get_tensors, autospec=True):
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ev = evaluator.ExpressionEvaluator(dump)
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self.assertAllClose([[-3.0], [1.0]],
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ev.evaluate("np.matmul(`a:0`, `b:0`)"))
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self.assertAllClose(
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[[-4.0], [2.0]], ev.evaluate("np.matmul(`a:0`, `b:0`) + `b:0`"))
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def testEvaluateNoneExistentTensorGeneratesError(self):
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dump = test.mock.MagicMock()
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def fake_get_tensors(node_name, output_slot, debug_op, device_name=None):
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del node_name, output_slot, debug_op, device_name # Unused.
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raise debug_data.WatchKeyDoesNotExistInDebugDumpDirError()
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with test.mock.patch.object(
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dump, "get_tensors", side_effect=fake_get_tensors, autospec=True):
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ev = evaluator.ExpressionEvaluator(dump)
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with self.assertRaisesRegexp(
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ValueError, "Eval failed due to the value of .* being unavailable"):
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ev.evaluate("np.matmul(`a:0`, `b:0`)")
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def testEvaluateWithMultipleDevicesContainingTheSameTensorName(self):
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dump = test.mock.MagicMock()
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def fake_get_tensors(node_name, output_slot, debug_op, device_name=None):
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del output_slot, debug_op # Unused.
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if node_name == "a" and device_name is None:
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raise ValueError(
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"There are multiple (2) devices with nodes named 'a' but "
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"device_name is not specified")
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elif (node_name == "a" and
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device_name == "/job:worker/replica:0/task:0/cpu:0"):
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return [np.array(10.0)]
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elif (node_name == "a" and
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device_name == "/job:worker/replica:0/task:1/cpu:0"):
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return [np.array(20.0)]
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with test.mock.patch.object(
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dump, "get_tensors", side_effect=fake_get_tensors, autospec=True):
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ev = evaluator.ExpressionEvaluator(dump)
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with self.assertRaisesRegexp(ValueError, r"multiple \(2\) devices"):
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ev.evaluate("`a:0` + `a:0`")
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self.assertAllClose(
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30.0,
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ev.evaluate("`/job:worker/replica:0/task:0/cpu:0:a:0` + "
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"`/job:worker/replica:0/task:1/cpu:0:a:0`"))
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def testEvaluateWithNonDefaultDebugOp(self):
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dump = test.mock.MagicMock()
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def fake_get_tensors(node_name, output_slot, debug_op, device_name=None):
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del device_name # Unused.
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if node_name == "a" and output_slot == 0 and debug_op == "DebugIdentity":
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return [np.array([[-1.0], [1.0]])]
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elif node_name == "a" and output_slot == 0 and debug_op == "DebugFoo":
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return [np.array([[-2.0, 2.0]])]
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with test.mock.patch.object(
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dump, "get_tensors", side_effect=fake_get_tensors, autospec=True):
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ev = evaluator.ExpressionEvaluator(dump)
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self.assertAllClose(
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[[4.0]],
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ev.evaluate("np.matmul(`a:0:DebugFoo`, `a:0:DebugIdentity`)"))
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def testEvaluateWithMultipleExecIndexes(self):
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dump = test.mock.MagicMock()
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def fake_get_tensors(node_name, output_slot, debug_op, device_name=None):
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del debug_op, device_name # Unused.
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if node_name == "a" and output_slot == 0:
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return [np.array([[-1.0], [1.0]]), np.array([[-2.0], [2.0]])]
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with test.mock.patch.object(
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dump, "get_tensors", side_effect=fake_get_tensors, autospec=True):
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ev = evaluator.ExpressionEvaluator(dump)
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self.assertAllClose(
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[[4.0]], ev.evaluate("np.matmul(`a:0[1]`.T, `a:0[0]`)"))
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def testEvaluateExpressionWithUnmatchedBacktick(self):
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dump = test.mock.MagicMock()
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ev = evaluator.ExpressionEvaluator(dump)
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with self.assertRaises(SyntaxError):
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ev.evaluate("np.matmul(`a:0`, `b:0`) + `b:0")
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def testEvaluateExpressionWithInvalidDebugTensorName(self):
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dump = test.mock.MagicMock()
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ev = evaluator.ExpressionEvaluator(dump)
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with self.assertRaisesRegexp(
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ValueError, r".* tensor name .* expression .* malformed"):
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ev.evaluate("np.matmul(`a`, `b`)")
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with self.assertRaisesRegexp(
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ValueError, r".* tensor name .* expression .* malformed"):
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ev.evaluate("np.matmul(`a:0:DebugIdentity:0`, `b:1:DebugNanCount:2`)")
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with self.assertRaises(ValueError):
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ev.evaluate("np.matmul(`a:0[]`, `b:0[]`)")
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if __name__ == "__main__":
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test.main()
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