-
Notifications
You must be signed in to change notification settings - Fork 3.6k
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Merge branch 'master' of https://github.com/onnx/onnx into neraoof/op…
…tional # Conflicts: # docs/Changelog.md # docs/TestCoverage.md # onnx/defs/operator_sets.h
- Loading branch information
Showing
90 changed files
with
706 additions
and
6 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,100 @@ | ||
# SPDX-License-Identifier: Apache-2.0 | ||
|
||
# coding: utf-8 | ||
|
||
from __future__ import absolute_import | ||
from __future__ import division | ||
from __future__ import print_function | ||
from __future__ import unicode_literals | ||
|
||
import numpy as np # type: ignore | ||
|
||
import onnx | ||
from onnx import TensorProto | ||
from onnx.mapping import TENSOR_TYPE_TO_NP_TYPE | ||
|
||
from ..base import Base | ||
from . import expect | ||
import sys | ||
|
||
|
||
class CastLike(Base): | ||
|
||
@staticmethod | ||
def export(): # type: () -> None | ||
shape = (3, 4) | ||
test_cases = [ | ||
('FLOAT', 'FLOAT16'), | ||
('FLOAT', 'DOUBLE'), | ||
('FLOAT16', 'FLOAT'), | ||
('FLOAT16', 'DOUBLE'), | ||
('DOUBLE', 'FLOAT'), | ||
('DOUBLE', 'FLOAT16'), | ||
('FLOAT', 'STRING'), | ||
('STRING', 'FLOAT'), | ||
('FLOAT', 'BFLOAT16'), | ||
('BFLOAT16', 'FLOAT'), | ||
] | ||
|
||
for from_type, to_type in test_cases: | ||
input_type_proto = None | ||
output_type_proto = None | ||
if 'BFLOAT16' == from_type or 'BFLOAT16' == to_type: | ||
np_fp32 = np.array([u'0.47892547', u'0.48033667', u'0.49968487', u'0.81910545', | ||
u'0.47031248', u'0.816468', u'0.21087195', u'0.7229038', | ||
u'NaN', u'INF', u'+INF', u'-INF'], dtype=np.float32) | ||
little_endisan = sys.byteorder == 'little' | ||
np_uint16_view = np_fp32.view(dtype=np.uint16) | ||
np_bfp16 = np_uint16_view[1::2] if little_endisan else np_uint16_view[0::2] | ||
if 'BFLOAT16' == to_type: | ||
assert from_type == 'FLOAT' | ||
input = np_fp32.reshape([3, 4]) | ||
output = np_bfp16.reshape([3, 4]) | ||
input_type = onnx.helper.make_tensor_type_proto(int(TensorProto.FLOAT), None) | ||
output_type_proto = onnx.helper.make_tensor_type_proto(int(TensorProto.BFLOAT16), None) | ||
else: | ||
assert to_type == 'FLOAT' | ||
input = np_bfp16.reshape([3, 4]) | ||
#convert bfloat to FLOAT | ||
np_fp32_zeros = np.zeros((len(np_bfp16) * 2,), dtype=np.uint16) | ||
if little_endisan: | ||
np_fp32_zeros[1::2] = np_bfp16 | ||
else: | ||
np_fp32_zeros[0::2] = np_bfp16 | ||
np_fp32_from_bfloat = np_fp32_zeros.view(dtype=np.float32) | ||
output = np_fp32_from_bfloat.reshape([3, 4]) | ||
input_type_proto = onnx.helper.make_tensor_type_proto(int(TensorProto.BFLOAT16), None) | ||
output_type_proto = onnx.helper.make_tensor_type_proto(int(TensorProto.FLOAT), None) | ||
elif 'STRING' != from_type: | ||
input = np.random.random_sample(shape).astype( | ||
TENSOR_TYPE_TO_NP_TYPE[getattr(TensorProto, from_type)]) | ||
if ('STRING' == to_type): | ||
# Converting input to str, then give it np.object dtype for generating script | ||
ss = [] | ||
for i in input.flatten(): | ||
s = str(i).encode('utf-8') | ||
su = s.decode('utf-8') | ||
ss.append(su) | ||
|
||
output = np.array(ss).astype(np.object).reshape([3, 4]) | ||
else: | ||
output = input.astype(TENSOR_TYPE_TO_NP_TYPE[getattr(TensorProto, to_type)]) | ||
else: | ||
input = np.array([u'0.47892547', u'0.48033667', u'0.49968487', u'0.81910545', | ||
u'0.47031248', u'0.816468', u'0.21087195', u'0.7229038', | ||
u'NaN', u'INF', u'+INF', u'-INF'], dtype=np.dtype(np.object)).reshape([3, 4]) | ||
output = input.astype(TENSOR_TYPE_TO_NP_TYPE[getattr(TensorProto, to_type)]) | ||
like = output.flatten()[0:1] | ||
node = onnx.helper.make_node( | ||
'CastLike', | ||
inputs=['input', 'like'], | ||
outputs=['output'], | ||
) | ||
if input_type_proto and output_type_proto: | ||
expect(node, inputs=[input, like], outputs=[output], | ||
name='test_castlike_' + from_type + '_to_' + to_type, | ||
input_type_protos=[input_type_proto, output_type_proto], | ||
output_type_protos=[output_type_proto]) | ||
else: | ||
expect(node, inputs=[input, like], outputs=[output], | ||
name='test_castlike_' + from_type + '_to_' + to_type) |
Oops, something went wrong.