def _nnefdog_to_source_impl(nnefdog,
file_handle,
custom_fragments="",
enable_shape_of=False):
# type: (NnefGraph, TextIO, str, bool)->TextIO
f = file_handle
fix_str = utils.ensure_not_unicode_in_python2
indent = 4 * " "
print(nnef.format_version((1, 0)), file=f)
extensions = []
if enable_shape_of:
extensions.append("KHR_enable_operator_expressions")
print(nnef.format_extensions(extensions), file=f)
print(file=f)
if custom_fragments:
print(custom_fragments, file=f)
print(file=f)
graph_params = nnef.format_graph(
name=fix_str(nnefdog.name),
inputs=[fix_str(name) for name in nnefdog.input_dn_names],
outputs=[fix_str(name) for name in nnefdog.output_dn_names])
print("graph {}".format(graph_params), file=f)
print("{", file=f)
for op in nnefdog.ops:
dtype = op.result.dtype if op.name in [
"external", "constant", "variable"
] else None
invocation = nnef.format_invocation(name=fix_str(op.name),
args=[],
kwargs=_preprocess_args(op.args),
results=_results_to_result_names(
op.results.values()),
dtype=dtype)
comments = utils.without_nones(
[dn.extra.get(dog.EXTRA_COMMENT) for dn in op.get_result_nodes()])
comment = " # {}".format(", ".join(comments)) if comments else ""
print("{}{};{}".format(indent, invocation, comment), file=f)
print("}", file=f)
return file_handle
def _nnefdog_to_source_impl(nnefdog, file_handle, custom_fragments=""):
# type: (NnefGraph, TextIO, str)->TextIO
f = file_handle
fix_str = utils.ensure_not_unicode_in_python2
indent = 4 * " "
print(nnef.format_version((1, 0)), file=f)
extensions = []
print(nnef.format_extensions(extensions), file=f)
print(file=f)
if custom_fragments:
print(custom_fragments, file=f)
print(file=f)
graph_name = fix_str(nnefdog.name)
graph_inputs = [fix_str(name) for name in nnefdog.input_dn_names]
graph_outputs = [fix_str(name) for name in nnefdog.output_dn_names]
print("graph {}({}) -> ({})".format(graph_name, ', '.join(graph_inputs),
', '.join(graph_outputs)),
file=f)
print("{", file=f)
for op in nnefdog.ops:
dtype = op.result.dtype if op.name in [
"external", "constant", "variable"
] else None
invocation = nnef.format_invocation(name=fix_str(op.name),
attribs=_preprocess_args(op.args),
inputs=tuple(),
outputs=_results_to_result_names(
op.results.values()),
dtype=dtype)
comments = utils.without_nones(
[op.extra.get(dog.EXTRA_COMMENT)] +
[dn.extra.get(dog.EXTRA_COMMENT) for dn in op.get_result_nodes()])
comment = " # {}".format(", ".join(comments)) if comments else ""
print("{}{};{}".format(indent, invocation, comment), file=f)
print("}", file=f)
return file_handle
def _print(graph, file, extensions, fragments, version_custom_ops,
annotate_shapes):
assert graph.is_sorted(), "graph must be topologically sorted"
assert all(tensor.name is not None or (tensor.producer is None and tensor.data is not None)
for tensor in graph.tensors), \
"all tensors must have names"
assert all(all(s is not None for s in op.attribs['shape'])
for op in graph.operations if op.type == 'external'), \
"external ops must not contain undefined shapes"
print(nnef.format_version((1, 0)), file=file)
if len(extensions):
print(file=file)
print(nnef.format_extensions(extensions), file=file)
if fragments:
print(file=file)
print(fragments, file=file)
print(file=file)
graph_name = as_str(graph.name) if graph.name is not None else "G"
graph_inputs = [as_str(item.name) for item in graph.inputs]
graph_outputs = [as_str(item.name) for item in graph.outputs]
print("graph {}({}) -> ({})".format(graph_name, ', '.join(graph_inputs),
', '.join(graph_outputs)),
file=file)
print("{", file=file)
versions = {}
for op in graph.operations:
assert all(isinstance(item, Tensor) for item in op.outputs)
inputs = ((from_numpy(item.data) if item.producer is None else
nnef.Identifier(as_str(item.name))) if isinstance(
item, Tensor) else item for item in op.inputs)
inputs = tuple(inputs) if isinstance(op.inputs,
tuple) else (list(inputs), )
outputs = (nnef.Identifier(as_str(item.name)) for item in op.outputs)
outputs = tuple(outputs) if isinstance(op.outputs,
tuple) else (list(outputs), )
attribs = {
as_str(key): value
for key, value in six.iteritems(op.attribs)
}
name = _next_version(
op.type, versions
) if op.type not in nnef.StandardOperations and version_custom_ops else op.type
dtype = attribs.get('dtype')
if dtype is not None:
dtype = _nnef_dtype(dtype)
del attribs['dtype']
for key, value in six.iteritems(attribs):
if isinstance(value, (type, np.dtype)):
attribs[key] = _nnef_dtype(value)
invocation = nnef.format_invocation(name=name,
dtype=dtype,
attribs=attribs,
inputs=inputs,
outputs=outputs)
annotation = " # " + ", ".join(_nnef_dtype(output.dtype) + str(output.shape) for output in op.outputs) \
if annotate_shapes else ''
print(" {};{}".format(invocation, annotation), file=file)
print("}", file=file)
def _print(
nnef_graph, # type: NNEFGraph
file_handle, # type: typing.TextIO
extensions=None, # type: typing.Optional[typing.List[str]]
fragments=None, # type: typing.Optional[str]
only_print_used_fragments=False, # type: bool
):
# type: (...)->None
generate_source_operations(nnef_graph)
nnef_graph.sort()
try:
if extensions is None:
extensions = []
if fragments is None:
fragments = ""
fragments = add_tflite_quantization_fragment_if_needed(
nnef_graph, fragments)
if only_print_used_fragments:
fragments = get_used_fragments(nnef_graph, fragments)
if fragments:
if "KHR_enable_fragment_definitions" not in extensions:
extensions.append("KHR_enable_fragment_definitions")
if "KHR_enable_operator_expressions" not in extensions:
extensions.append("KHR_enable_operator_expressions")
f = file_handle
indent = 4 * " "
print(nnef.format_version((1, 0)), file=f)
if extensions:
print(nnef.format_extensions(extensions), file=f)
if fragments:
print(file=f)
print(fragments, file=f)
print(file=f)
graph_name = _recursive_check_str(
nnef_graph.name) if nnef_graph.name is not None else "network"
graph_inputs = _recursive_check_str(
[input_.name for input_ in nnef_graph.inputs])
graph_outputs = _recursive_check_str(
[output_.name for output_ in nnef_graph.outputs])
print("graph {}({}) -> ({})".format(graph_name,
', '.join(graph_inputs),
', '.join(graph_outputs)),
file=f)
print("{", file=f)
for op in nnef_graph.operations:
inputs = _transform_inputs_before_print(
list(op.inputs) if not isinstance(op.inputs, tuple) else op.
inputs)
dtype = op.output.dtype if op.name in [
"external", "constant", "variable"
] else None
invocation = nnef.format_invocation(
name=_recursive_check_str(op.name),
attribs=_recursive_check_str(_sorted_ordered_dict(op.attribs)),
inputs=_recursive_check_str(
[inputs] if isinstance(inputs, list) else list(inputs)),
outputs=_recursive_check_str(
_result_to_identifiers(
list(op.outputs)
if not isinstance(op.outputs, tuple) else op.outputs)),
dtype=_recursive_check_str(dtype))
comment = " # {}".format(_recursive_check_str(
op.comment)) if op.comment else ""
print("{}{};{}".format(indent, invocation, comment), file=f)
print("}", file=f)
finally:
remove_source_operations(nnef_graph)
