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celinelee
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python_fn_calls

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exists()
_os.path.exists(_toco_from_proto_bin)
_try_convert_to_unicode(output)
isinstance(output, bytes)
six.ensure_text(output)
_tf_export("lite.OpsSet")
OpsSet(enum.Enum)
__str__(self)
get_options()
str(option)
list(OpsSet)
ConverterError(Exception)
form (e.g. a graphdef is common)
information. (default None)
conversion. (default False)
form (e.g. a TFLITE model is common)
TODO(aselle)
ConverterError(str(e)
_tempfile.NamedTemporaryFile(delete=False)
_tempfile.NamedTemporaryFile(delete=False)
_tempfile.NamedTemporaryFile(delete=False)
_tempfile.NamedTemporaryFile(delete=False)
fp_model.write(model_flags_str)
fp_toco.write(toco_flags_str)
fp_input.write(six.ensure_binary(input_data_str)
fp_debug.write(debug_info_str)
isinstance(debug_info_str, bytes)
fp_debug.write(debug_info_str.encode("utf-8")
fp_debug.write(debug_info_str)
_tempfile.NamedTemporaryFile(delete=False)
format(debug_filename)
cmd.append("--enable_mlir_converter")
join(cmd)
_platform.system()
proc.communicate()
open(output_filename, "rb")
fp.read()
_try_convert_to_unicode(stdout)
_try_convert_to_unicode(stderr)
ConverterError("See console for info.\n%s\n%s\n" % (stdout, stderr)
_os.unlink(filename)
except (OSError, TypeError)
tensors (only .name is used from this)
None. (default None)
std_dev_value. (default None)
representing (min, max)
dependencies. (default True)
behavior. (default False)
resolver. (default False)
converter. (default None)
true. (default False)
improvements (at the cost of accuracy)
float16. (default False)
file. (default None)
transformation. (default False)
use. (default set([OpsSet.TFLITE_BUILTINS])
graph. (default False)
_toco_flags_pb2.TocoFlags()
util.convert_dtype_to_tflite_type(inference_type)
toco.custom_opdefs.extend(custom_opdefs)
set(target_ops)
set([OpsSet.TFLITE_BUILTINS, OpsSet.SELECT_TF_OPS])
set(target_ops)
set([OpsSet.SELECT_TF_OPS])
_model_flags_pb2.ModelFlags()
enumerate(input_tensors)
model.input_arrays.add()
util.get_tensor_name(input_tensor)
input_array.shape.dims.extend(list(map(int, shape)
model.output_arrays.append(util.get_tensor_name(output_tensor)
data (i.e. often `sess.graph_def`)
shapes (e.g., [("foo" : [1, 16, 16, 3])
None. (default None)
None. (default None)
enumerate(input_arrays_with_shape)
model_flags.input_arrays.add()
if (("quantized_input_stats" not in kwargs)
or (not kwargs["quantized_input_stats"])
input_array.shape.dims.extend(list(map(int, shape)
model_flags.output_arrays.append(name)
model_flags.SerializeToString()
toco_flags.SerializeToString()
input_data.SerializeToString()
data (i.e. often `sess.graph_def`)
tensors (only .name is used from this)
debug_info.SerializeToString()
model_flags.SerializeToString()
toco_flags.SerializeToString()
input_data.SerializeToString()
_tf_export(v1=["lite.toco_convert"])
deprecation.deprecated(None, "Use `lite.TFLiteConverter` instead.")
toco_convert(input_data, input_tensors, output_tensors, *args, **kwargs)
data (i.e. often `sess.graph_def`)
tensors (only .name is used from this)
kwargs.get("enable_mlir_converter", False)
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)
found_shiny_text(found_pokemon = '', to_num = twilioConfig.to_phone_number, from_num = twilioConfig.from_phone_number)
found_shiny_call(to_num, from_num)
Number (example: '+12223333333')
Client(account_sid, auth_token)