def test_remove_duplication_with_crops(self):
graph = build_graph({'input': {'kind': 'op', 'op': 'Parameter'},
'in_node': {'kind': 'data', 'shape': [1, 13]},
'splice_1': {'kind': 'op', 'op': 'Splice', 'context': range(-5, 6)},
'splice_data_1': {'kind': 'data', 'shape': [1, 143]},
'crop_1': {'kind': 'op', 'op': 'Crop', 'offset': 13, 'dim': 13, 'axis': -1},
'splice_2': {'kind': 'op', 'op': 'Splice', 'context': range(-1, 2)},
'splice_data_2': {'kind': 'data', 'shape': [1, 39]},
'crop_2': {'kind': 'op', 'op': 'Crop', 'offset': 13, 'dim': 13, 'axis': -1},
},
[('input', 'in_node'), ('in_node', 'splice_1'),
('splice_1', 'splice_data_1'), ('splice_data_1', 'crop_1'),
('in_node', 'splice_2'), ('splice_2', 'splice_data_2'), ('splice_data_2', 'crop_2'),
],
nodes_with_edges_only=True)
RemoveMemoryDuplicationPattern().find_and_replace_pattern(graph)
ref_graph = build_graph({'input': {'kind': 'op', 'op': 'Parameter'},
'in_node': {'kind': 'data', 'shape': [1, 13]},
'splice_1': {'kind': 'op', 'op': 'Splice', 'context': range(-5, 6)},
'splice_data_1': {'kind': 'data', 'shape': [1, 143]},
'crop_1': {'kind': 'op', 'op': 'Crop', 'offset': 13, 'dim': 13},
'crop_2': {'kind': 'op', 'op': 'Crop', 'offset': 65, 'dim': 13, 'axis': -1},
},
[
('input', 'in_node'), ('in_node', 'splice_1'),
('splice_1', 'splice_data_1'),
('splice_data_1', 'crop_1'), ('splice_data_1', 'crop_2'),
],
nodes_with_edges_only=True
)
(flag, resp) = compare_graphs(graph, ref_graph, 'crop_2')
self.assertTrue(flag, resp)
def driver(argv, input_model, output_model_name, output_dir):
log_step(argv.steps, 'LOAD')
meta_info = get_meta_info(argv)
EltwiseChecker.enabled = False
try:
graph = load_kaldi_model(input_model)
except Exception as e:
raise Error('Model Optimizer is not able to parse Kaldi model {}. '.format(input_model) +
refer_to_faq_msg(91)) from e
graph.check_empty_graph('load_kaldi_nnet_model')
graph.graph['cmd_params'] = argv
graph.graph['fw'] = 'kaldi'
if graph.graph['cmd_params'].generate_experimental_IR_V10:
version = 10
else:
version = 6
graph.graph['ir_version'] = 2 if argv.generate_deprecated_IR_V2 else version
update_extractors_with_extensions(kaldi_type_extractors)
extract_node_attrs(graph, lambda node: kaldi_extractor(node))
# --------------------------------- LOAD END ------------------------------------------------------
log_step(argv.steps, 'FRONT')
ReplaceLSTMNodePattern().find_and_replace_pattern(graph)
class_registration.apply_replacements(graph, class_registration.ClassType.FRONT_REPLACER)
log_step(argv.steps, 'MIDDLE')
graph = partial_infer(graph)
ReplacePNormNodePattern().find_and_replace_pattern(graph)
ReplaceMemoryOffsetNodePattern().find_and_replace_pattern(graph)
ReplaceMemoryOffsetWithMemoryNodePattern().find_and_replace_pattern(graph)
RemoveMemoryDuplicationPattern().find_and_replace_pattern(graph)
MergeNeighborSplicePattern().find_and_replace_pattern(graph)
RemoveUselessCropsPattern().find_and_replace_pattern(graph)
RemoveIdentity().find_and_replace_pattern(graph)
graph_clean_up(graph)
AddSelectBeforeMemoryNodePattern().find_and_replace_pattern(graph)
ReplaceSpliceNodePattern().find_and_replace_pattern(graph)
graph_clean_up(graph)
# The order is intentional, firstly eliminate repeated, then remove redundant
FuseRepeatedReshapes().find_and_replace_pattern(graph)
EliminateRedundantReshape().find_and_replace_pattern(graph)
graph_clean_up(graph)
graph.check_empty_graph('partial_infer')
if argv.counts:
try:
counts = read_counts_file(argv.counts)
except Exception as e:
raise Error('Model Optimizer is not able to read counts file {}'.format(argv.counts) +
refer_to_faq_msg(92)) from e
apply_biases_to_last_layer(graph, counts)
if argv.remove_output_softmax:
RemoveLastSoftMaxPattern().find_and_replace_pattern(graph)
graph_clean_up(graph)
log.debug("After removing softmax")
graph.print_graph_stat()
log_step(argv.steps, 'BACK')
LeakyReluToReluWithNegativeSlope().find_and_replace_pattern(graph)
TransposeToPermute().find_and_replace_pattern(graph)
DivideToEltwises().find_and_replace_pattern(graph)
SubtractToEltwises().find_and_replace_pattern(graph)
SimpleEltwiseToEltwiseOp().find_and_replace_pattern(graph)
for_graph_and_each_sub_graph_recursively(graph, convert_matmul_to_fully_connected)
# Intentionally after all transformations
if argv.remove_memory:
CutMemory().find_and_replace_pattern(graph)
graph_clean_up(graph)
ParameterToInput().find_and_replace_pattern(graph)
KaldiRemoveMemoryOutputBackReplacementPattern().find_and_replace_pattern(graph)
ForceStrictPrecision().find_and_replace_pattern(graph)
remove_const_ops(graph)
CreateConstNodesReplacement().find_and_replace_pattern(graph)
remove_output_ops(graph)
log_step(argv.steps, 'EMIT')
prepare_emit_ir(graph, argv.data_type, output_dir, output_model_name, meta_info=meta_info)
return 0