def testSelectEverything(self): ops.reset_default_graph() opts = model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS outfile = os.path.join(test.get_temp_dir(), 'dump') opts['output'] = 'file:outfile=' + outfile opts['account_type_regexes'] = ['.*'] opts['select'] = [ 'bytes', 'params', 'float_ops', 'num_hidden_ops', 'device', 'op_types' ] with session.Session() as sess, ops.device('/cpu:0'): x = lib.BuildSmallModel() sess.run(variables.global_variables_initializer()) run_meta = config_pb2.RunMetadata() _ = sess.run(x, options=config_pb2.RunOptions( trace_level=config_pb2.RunOptions.FULL_TRACE), run_metadata=run_meta) model_analyzer.print_model_analysis(sess.graph, run_meta, tfprof_options=opts) with gfile.Open(outfile, 'r') as f: # pylint: disable=line-too-long self.assertEqual( '_TFProfRoot (0/451 params, 0/10.44k flops, 0B/5.28KB, _kTFScopeParent)\n Conv2D (0/0 params, 5.83k/5.83k flops, 432B/432B, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Conv2D)\n Conv2D_1 (0/0 params, 4.61k/4.61k flops, 384B/384B, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Conv2D)\n DW (3x3x3x6, 162/162 params, 0/0 flops, 648B/1.30KB, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|VariableV2|_trainable_variables)\n DW/Assign (0/0 params, 0/0 flops, 0B/0B, Assign)\n DW/Initializer (0/0 params, 0/0 flops, 0B/0B, _kTFScopeParent)\n DW/Initializer/random_normal (0/0 params, 0/0 flops, 0B/0B, Add)\n DW/Initializer/random_normal/RandomStandardNormal (0/0 params, 0/0 flops, 0B/0B, RandomStandardNormal)\n DW/Initializer/random_normal/mean (0/0 params, 0/0 flops, 0B/0B, Const)\n DW/Initializer/random_normal/mul (0/0 params, 0/0 flops, 0B/0B, Mul)\n DW/Initializer/random_normal/shape (0/0 params, 0/0 flops, 0B/0B, Const)\n DW/Initializer/random_normal/stddev (0/0 params, 0/0 flops, 0B/0B, Const)\n DW/read (0/0 params, 0/0 flops, 648B/648B, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Identity)\n DW2 (2x2x6x12, 288/288 params, 0/0 flops, 1.15KB/2.30KB, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|VariableV2|_trainable_variables)\n DW2/Assign (0/0 params, 0/0 flops, 0B/0B, Assign)\n DW2/Initializer (0/0 params, 0/0 flops, 0B/0B, _kTFScopeParent)\n DW2/Initializer/random_normal (0/0 params, 0/0 flops, 0B/0B, Add)\n DW2/Initializer/random_normal/RandomStandardNormal (0/0 params, 0/0 flops, 0B/0B, RandomStandardNormal)\n DW2/Initializer/random_normal/mean (0/0 params, 0/0 flops, 0B/0B, Const)\n DW2/Initializer/random_normal/mul (0/0 params, 0/0 flops, 0B/0B, Mul)\n DW2/Initializer/random_normal/shape (0/0 params, 0/0 flops, 0B/0B, Const)\n DW2/Initializer/random_normal/stddev (0/0 params, 0/0 flops, 0B/0B, Const)\n DW2/read (0/0 params, 0/0 flops, 1.15KB/1.15KB, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Identity)\n ScalarW (1, 1/1 params, 0/0 flops, 0B/0B, VariableV2|_trainable_variables)\n ScalarW/Assign (0/0 params, 0/0 flops, 0B/0B, Assign)\n ScalarW/Initializer (0/0 params, 0/0 flops, 0B/0B, _kTFScopeParent)\n ScalarW/Initializer/random_normal (0/0 params, 0/0 flops, 0B/0B, Add)\n ScalarW/Initializer/random_normal/RandomStandardNormal (0/0 params, 0/0 flops, 0B/0B, RandomStandardNormal)\n ScalarW/Initializer/random_normal/mean (0/0 params, 0/0 flops, 0B/0B, Const)\n ScalarW/Initializer/random_normal/mul (0/0 params, 0/0 flops, 0B/0B, Mul)\n ScalarW/Initializer/random_normal/shape (0/0 params, 0/0 flops, 0B/0B, Const)\n ScalarW/Initializer/random_normal/stddev (0/0 params, 0/0 flops, 0B/0B, Const)\n ScalarW/read (0/0 params, 0/0 flops, 0B/0B, Identity)\n init (0/0 params, 0/0 flops, 0B/0B, NoOp)\n zeros (0/0 params, 0/0 flops, 864B/864B, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Const)\n', f.read())
def testCodeViewLeafGraphNode(self): ops.reset_default_graph() opts = model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS.copy() opts['account_type_regexes'] = ['.*'] opts['account_displayed_op_only'] = False opts['select'] = [ 'bytes', 'params', 'float_ops', 'num_hidden_ops', 'device' ] with session.Session() as sess, ops.device('/cpu:0'): x = lib.BuildSmallModel() sess.run(variables.global_variables_initializer()) run_meta = config_pb2.RunMetadata() _ = sess.run(x, options=config_pb2.RunOptions( trace_level=config_pb2.RunOptions.FULL_TRACE), run_metadata=run_meta) tfprof_node = model_analyzer.print_model_analysis( sess.graph, run_meta, tfprof_cmd='code', tfprof_options=opts) leaf = tfprof_node while leaf.children: self.assertEqual(0, len(leaf.graph_nodes)) leaf = leaf.children[0] self.assertEqual(1, len(leaf.graph_nodes))
def testSimpleCodeView(self): ops.reset_default_graph() opts = model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS.copy() outfile = os.path.join(test.get_temp_dir(), 'dump') opts['output'] = 'file:outfile=' + outfile opts['account_type_regexes'] = ['.*'] opts['show_name_regexes'] = ['.*model_analyzer_testlib.*'] opts['account_displayed_op_only'] = False # TODO(xpan): Test 'micros'. Since the execution time changes each run, # it's a bit difficult to test it now. opts['select'] = [ 'bytes', 'params', 'float_ops', 'num_hidden_ops', 'device', ] with session.Session() as sess, ops.device('/cpu:0'): x = lib.BuildSmallModel() sess.run(variables.global_variables_initializer()) run_meta = config_pb2.RunMetadata() _ = sess.run(x, options=config_pb2.RunOptions( trace_level=config_pb2.RunOptions.FULL_TRACE), run_metadata=run_meta) model_analyzer.print_model_analysis( sess.graph, run_meta, tfprof_cmd='code', tfprof_options=opts) with gfile.Open(outfile, 'r') as f: # pylint: disable=line-too-long self.assertEqual('_TFProfRoot (', f.read()[0:13])
def testDumpToFile(self): ops.reset_default_graph() opts = model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS outfile = os.path.join(test.get_temp_dir(), 'dump') opts['output'] = 'file:outfile=' + outfile with session.Session() as sess, ops.device('/cpu:0'): _ = lib.BuildSmallModel() model_analyzer.print_model_analysis(sess.graph, tfprof_options=opts) with gfile.Open(outfile, 'r') as f: self.assertEqual(u'_TFProfRoot (--/451 params)\n' ' DW (3x3x3x6, 162/162 params)\n' ' DW2 (2x2x6x12, 288/288 params)\n' ' ScalarW (1, 1/1 params)\n', f.read())
def testSimpleCodeView(self): ops.reset_default_graph() opts = model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS.copy() opts['dump_to_file'] = os.path.join(test.get_temp_dir(), 'dump') opts['account_type_regexes'] = ['.*'] opts['show_name_regexes'] = ['.*model_analyzer_testlib.*'] opts['account_displayed_op_only'] = False # TODO(xpan): Test 'micros'. Since the execution time changes each run, # it's a bit difficult to test it now. opts['select'] = [ 'bytes', 'params', 'float_ops', 'num_hidden_ops', 'device', ] config = config_pb2.ConfigProto(graph_options=config_pb2.GraphOptions( build_cost_model=1)) with session.Session(config=config) as sess, ops.device('/cpu:0'): x = lib.BuildSmallModel() sess.run(variables.global_variables_initializer()) run_meta = config_pb2.RunMetadata() _ = sess.run(x, options=config_pb2.RunOptions( trace_level=config_pb2.RunOptions.FULL_TRACE), run_metadata=run_meta) model_analyzer.print_model_analysis(sess.graph, run_meta, tfprof_cmd='code', tfprof_options=opts) with gfile.Open(opts['dump_to_file'], 'r') as f: # pylint: disable=line-too-long self.assertEqual( '_TFProfRoot (0/451 params, 0/10.44k flops, 0B/5.28KB)\n model_analyzer_testlib.py:33:BuildSmallModel:image = array_ops... (0/0 params, 0/0 flops, 0B/864B)\n model_analyzer_testlib.py:37:BuildSmallModel:initializer=init_... (0/1 params, 0/0 flops, 0B/0B)\n model_analyzer_testlib.py:41:BuildSmallModel:initializer=init_... (0/162 params, 0/0 flops, 0B/1.30KB)\n model_analyzer_testlib.py:42:BuildSmallModel:x = nn_ops.conv2d... (0/0 params, 0/5.83k flops, 0B/432B)\n model_analyzer_testlib.py:46:BuildSmallModel:initializer=init_... (0/288 params, 0/0 flops, 0B/2.30KB)\n model_analyzer_testlib.py:47:BuildSmallModel:x = nn_ops.conv2d... (0/0 params, 0/4.61k flops, 0B/384B)\n', f.read())