def test_pnorm(self):
graph = build_graph(self.nodes_attributes,
[('placeholder', 'in_node'), ('in_node', 'pnorm'),
('pnorm', 'pnorm_data'),
('pnorm_data', 'out_placeholder')])
ReplacePNormNodePattern().find_and_replace_pattern(graph)
ref_graph = build_graph(
{
'in_placeholder': {
'kind': 'op',
'op': None
},
'in_node': {
'kind': 'data',
'shape': [1, 3500]
},
'pow_const': {
'kind': 'op',
'value': 2.0
},
'pow_const_d': {
'kind': 'data'
},
'pow': {
'kind': 'op',
'op': 'Pow'
},
'pow_data': {
'kind': 'data'
},
'reshape': {
'kind': 'op',
'op': 'Reshape'
},
'reshape_data': {
'kind': 'data'
},
'const': {
'kind': 'op',
'op': 'Const',
'value': [1, 350, 10]
},
'const_data': {
'kind': 'data'
},
'reduce': {
'kind': 'op',
'op': 'ReduceSum'
},
'reduce_data': {
'kind': 'data'
},
'const_1': {
'kind': 'op',
'op': 'Const',
'value': 2
},
'const_data_1': {
'kind': 'data'
},
'invpow_const': {
'kind': 'op',
'value': 0.5
},
'invpow_const_d': {
'kind': 'data'
},
'invpow': {
'kind': 'op',
'op': 'Pow'
},
'invpow_data': {
'kind': 'data'
},
'out_placeholder': {
'kind': 'op',
'op': 'placeholder'
},
}, [
('in_placeholder', 'in_node'),
('in_node', 'pow', {
'in': 0
}),
('pow', 'pow_data'),
('pow_data', 'reshape', {
'in': 0
}),
('reshape', 'reshape_data'),
('const', 'const_data'),
('const_data', 'reshape', {
'in': 1
}),
('reshape_data', 'reduce', {
'in': 0
}),
('const_1', 'const_data_1'),
('const_data_1', 'reduce', {
'in': 1
}),
('reduce', 'reduce_data'),
('reduce_data', 'invpow', {
'in': 0
}),
('invpow', 'invpow_data'),
('invpow_data', 'out_placeholder'),
('pow_const', 'pow_const_d'),
('invpow_const', 'invpow_const_d'),
('pow_const_d', 'pow', {
'in': 1
}),
('invpow_const_d', 'invpow', {
'in': 1
}),
])
(flag, resp) = compare_graphs(graph,
ref_graph,
'out_placeholder',
check_op_attrs=True)
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