зеркало из https://github.com/microsoft/MMdnn.git
This commit is contained in:
Kit
Родитель
6fe9db3174
Коммит
3a0aeb69ea
|
|
@ -1,13 +1,10 @@
|
|||
import os
|
||||
import sys
|
||||
import six
|
||||
import unittest
|
||||
import numpy as np
|
||||
import tensorflow as tf
|
||||
from mmdnn.conversion.examples.imagenet_test import TestKit
|
||||
|
||||
from mmdnn.conversion.cntk.cntk_emitter import CntkEmitter
|
||||
from mmdnn.conversion.tensorflow.tensorflow_emitter import TensorflowEmitter
|
||||
from mmdnn.conversion.keras.keras2_emitter import Keras2Emitter
|
||||
from mmdnn.conversion.pytorch.pytorch_emitter import PytorchEmitter
|
||||
from mmdnn.conversion.mxnet.mxnet_emitter import MXNetEmitter
|
||||
|
|
@ -213,12 +210,16 @@ class TestModels(CorrectnessTest):
|
|||
|
||||
@staticmethod
|
||||
def TensorflowEmit(original_framework, architecture_name, architecture_path, weight_path, image_path):
|
||||
import tensorflow as tf
|
||||
from mmdnn.conversion.tensorflow.tensorflow_emitter import TensorflowEmitter
|
||||
|
||||
# IR to code
|
||||
converted_file = original_framework + '_tensorflow_' + architecture_name + "_converted"
|
||||
converted_file = converted_file.replace('.', '_')
|
||||
emitter = TensorflowEmitter((architecture_path, weight_path))
|
||||
emitter.run(converted_file + '.py', None, 'test')
|
||||
del emitter
|
||||
del TensorflowEmitter
|
||||
|
||||
# import converted model
|
||||
model_converted = __import__(converted_file).KitModel(weight_path)
|
||||
|
|
@ -235,6 +236,9 @@ class TestModels(CorrectnessTest):
|
|||
del sys.modules[converted_file]
|
||||
os.remove(converted_file + '.py')
|
||||
converted_predict = np.squeeze(predict)
|
||||
|
||||
del tf
|
||||
|
||||
return converted_predict
|
||||
|
||||
|
||||
|
|
@ -262,13 +266,14 @@ class TestModels(CorrectnessTest):
|
|||
|
||||
predict = model_converted(input_data)
|
||||
predict = predict.data.numpy()
|
||||
converted_predict = np.squeeze(predict)
|
||||
|
||||
del model_converted
|
||||
del sys.modules[converted_file]
|
||||
del torch
|
||||
os.remove(converted_file + '.py')
|
||||
os.remove(converted_file + '.npy')
|
||||
converted_predict = np.squeeze(predict)
|
||||
|
||||
return converted_predict
|
||||
|
||||
|
||||
|
|
@ -342,47 +347,47 @@ class TestModels(CorrectnessTest):
|
|||
'cntk' : {
|
||||
# 'alexnet' : [TensorflowEmit, KerasEmit],
|
||||
# 'resnet18' : [TensorflowEmit, KerasEmit],
|
||||
'inception_v3' : [PytorchEmit ],
|
||||
'inception_v3' : [PytorchEmit],
|
||||
},
|
||||
|
||||
'keras' : {
|
||||
'vgg16' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit],
|
||||
'vgg16' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit],
|
||||
'vgg19' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit],
|
||||
'vgg19' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit],
|
||||
'inception_v3' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit],
|
||||
'resnet50' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit],
|
||||
'densenet' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit],
|
||||
'vgg19' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit],
|
||||
'inception_v3' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit],
|
||||
'resnet50' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit],
|
||||
'densenet' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit],
|
||||
'xception' : [TensorflowEmit, KerasEmit],
|
||||
'mobilenet' : [TensorflowEmit, KerasEmit],
|
||||
'mobilenet' : [TensorflowEmit, KerasEmit, MXNetEmit],
|
||||
'nasnet' : [TensorflowEmit, KerasEmit],
|
||||
},
|
||||
|
||||
'mxnet' : {
|
||||
'vgg19' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit],
|
||||
'imagenet1k-inception-bn' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit],
|
||||
'imagenet1k-resnet-152' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit],
|
||||
'squeezenet_v1.1' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit],
|
||||
'imagenet1k-resnext-101-64x4d' : [CntkEmit, TensorflowEmit, PytorchEmit], # Keras is too slow
|
||||
'imagenet1k-resnext-50' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit],
|
||||
'vgg19' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit],
|
||||
'imagenet1k-inception-bn' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit],
|
||||
'imagenet1k-resnet-152' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit],
|
||||
'squeezenet_v1.1' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit],
|
||||
'imagenet1k-resnext-101-64x4d' : [CntkEmit, TensorflowEmit, PytorchEmit, MXNetEmit], # Keras is too slow
|
||||
'imagenet1k-resnext-50' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit],
|
||||
},
|
||||
|
||||
'caffe' : {
|
||||
'vgg19' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit],
|
||||
'vgg19' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit],
|
||||
'alexnet' : [CntkEmit],
|
||||
'inception_v1' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit],
|
||||
'resnet152' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit],
|
||||
'squeezenet' : [CntkEmit, PytorchEmit]
|
||||
'inception_v1' : [CntkEmit, TensorflowEmit, KerasEmit, MXNetEmit], # TODO: PytorchEmit
|
||||
'resnet152' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit],
|
||||
'squeezenet' : [CntkEmit, PytorchEmit, MXNetEmit]
|
||||
},
|
||||
|
||||
'tensorflow' : {
|
||||
'vgg19' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit],
|
||||
'inception_v1' : [TensorflowEmit, KerasEmit, PytorchEmit], # TODO: CntkEmit
|
||||
'inception_v3' : [CntkEmit, TensorflowEmit, KerasEmit], # TODO: PytorchEmit
|
||||
'resnet_v1_50' : [TensorflowEmit, KerasEmit, PytorchEmit], # TODO: CntkEmit
|
||||
'resnet_v1_152' : [TensorflowEmit, KerasEmit, PytorchEmit], # TODO: CntkEmit
|
||||
'resnet_v2_50' : [TensorflowEmit, KerasEmit, PytorchEmit], # TODO: CntkEmit
|
||||
'resnet_v2_152' : [TensorflowEmit, KerasEmit, PytorchEmit], # TODO: CntkEmit
|
||||
'mobilenet_v1_1.0' : [TensorflowEmit, KerasEmit],
|
||||
'vgg19' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit],
|
||||
'inception_v1' : [TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit], # TODO: CntkEmit
|
||||
'inception_v3' : [CntkEmit, TensorflowEmit, KerasEmit, MXNetEmit], # TODO: PytorchEmit
|
||||
'resnet_v1_50' : [TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit], # TODO: CntkEmit
|
||||
'resnet_v1_152' : [TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit], # TODO: CntkEmit
|
||||
'resnet_v2_50' : [TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit], # TODO: CntkEmit
|
||||
'resnet_v2_152' : [TensorflowEmit, KerasEmit, PytorchEmit, MXNetEmit], # TODO: CntkEmit
|
||||
'mobilenet_v1_1.0' : [TensorflowEmit, KerasEmit, MXNetEmit],
|
||||
# 'inception_resnet_v2' : [CntkEmit, TensorflowEmit, KerasEmit, PytorchEmit], # TODO
|
||||
# 'nasnet-a_large' : [TensorflowEmit, KerasEmit, PytorchEmit], # TODO
|
||||
},
|
||||
|
|
@ -394,16 +399,16 @@ class TestModels(CorrectnessTest):
|
|||
ensure_dir(self.tmpdir)
|
||||
|
||||
for network_name in self.test_table[original_framework].keys():
|
||||
# print("Test {} from {} start.".format(network_name, original_framework), file=sys.stderr, flush=True)
|
||||
print("Test {} from {} start.".format(network_name, original_framework))
|
||||
print("Test {} from {} start.".format(network_name, original_framework), file=sys.stderr, flush=True)
|
||||
# print("Test {} from {} start.".format(network_name, original_framework))
|
||||
|
||||
# get original model prediction result
|
||||
original_predict = parser(network_name, self.image_path)
|
||||
|
||||
IR_file = TestModels.tmpdir + original_framework + '_' + network_name + "_converted"
|
||||
for emit in self.test_table[original_framework][network_name]:
|
||||
# print('Testing {} from {} to {}.'.format(network_name, original_framework, emit.__func__.__name__[:-4]), file=sys.stderr, flush=True)
|
||||
print('Testing {} from {} to {}.'.format(network_name, original_framework, emit.__func__.__name__[:-4]))
|
||||
print('Testing {} from {} to {}.'.format(network_name, original_framework, emit.__func__.__name__[:-4]), file=sys.stderr, flush=True)
|
||||
# print('Testing {} from {} to {}.'.format(network_name, original_framework, emit.__func__.__name__[:-4]))
|
||||
converted_predict = emit.__func__(
|
||||
original_framework,
|
||||
network_name,
|
||||
|
|
@ -413,8 +418,8 @@ class TestModels(CorrectnessTest):
|
|||
|
||||
self._compare_outputs(original_predict, converted_predict)
|
||||
|
||||
# print('Conversion {} from {} to {} passed.'.format(network_name, original_framework, emit.__func__.__name__[:-4]), file=sys.stderr, flush=True)
|
||||
print('Conversion {} from {} to {} passed.'.format(network_name, original_framework, emit.__func__.__name__[:-4]))
|
||||
print('Conversion {} from {} to {} passed.'.format(network_name, original_framework, emit.__func__.__name__[:-4]), file=sys.stderr, flush=True)
|
||||
# print('Conversion {} from {} to {} passed.'.format(network_name, original_framework, emit.__func__.__name__[:-4]))
|
||||
try:
|
||||
os.remove(IR_file + ".json")
|
||||
except OSError:
|
||||
|
|
@ -442,5 +447,5 @@ class TestModels(CorrectnessTest):
|
|||
self._test_function('keras', self.KerasParse)
|
||||
|
||||
|
||||
def test_mxnet(self):
|
||||
self._test_function('mxnet', self.MXNetParse)
|
||||
# def test_mxnet(self):
|
||||
# self._test_function('mxnet', self.MXNetParse)
|
||||
|
|
|
|||
Загрузка…
Ссылка в новой задаче