Python BatchNormGrad Examples

Example #1

File: test_batchnorm_grad.py Project: yrpang/mindspore

 def __init__(self, is_training):
     super(Net, self).__init__()
     self.fused_bn_grad_ex = G.BatchNormGrad(is_training=is_training, epsilon=1e-5)

Example #2

#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
from mindspore.ops import Primitive
from mindspore.ops.operations import _grad_ops as G
from mindspore.ops import _constants as Constants

make_tuple = Primitive('MakeTuple')
tuple_getitem = Primitive(Constants.kTupleGetItem)
BatchNormGradTraining = G.BatchNormGrad(is_training=True)
BatchNormGradInfer = G.BatchNormGrad(is_training=False)
BNInferGrad = Primitive('BNInferGrad')
BNTrainingUpdateGrad = Primitive('BNTrainingUpdateGrad')


class FnDict:
    def __init__(self):
        self.fnDict = {}

    def __call__(self, fn):
        self.fnDict[fn.__name__] = fn

    def __getitem__(self, name):
        return self.fnDict[name]

Example #3

File: test_ops.py Project: smartxcat/mindspore

     'block': P.FusedBatchNorm(),
     'desc_inputs': [[128, 64, 32, 64], [64], [64], [64], [64]],
     'desc_bprop': [[128, 64, 32, 64], [64], [64], [64], [64]],
     'skip': []}),
 ('FusedBatchNormGrad', {
     'block': G.FusedBatchNormGrad(),
     'desc_inputs': [[128, 64, 32, 64], [128, 64, 32, 64], [64], [64], [64]],
     'desc_bprop': [[128, 64, 32, 64], [64], [64], [64], [64]],
     'skip': ['backward']}),
 ('BatchNorm', {
     'block': P.BatchNorm(),
     'desc_inputs': [[128, 64, 32, 32], [64], [64], [64], [64]],
     'desc_bprop': [[128, 64, 32, 32], [64], [64], [64], [64]],
     'skip': []}),
 ('BatchNormGrad', {
     'block': G.BatchNormGrad(),
     'desc_inputs': [[128, 64, 32, 32], [128, 64, 32, 32], [64], [64], [64], [64]],
     'desc_bprop': [[128, 64, 32, 32], [64], [64], [64], [64]],
     'skip': ['backward']}),
 ('ApplyMomentum', {
     'block': P.ApplyMomentum(),
     'desc_inputs': [[128, 32, 32, 64], [128, 32, 32, 64],
                     [32, 32, 64], [32, 32, 64], [32, 32, 64]],
     'desc_bprop': [[128, 32, 32, 64]],
     'skip': ['backward']}),
 ('TopK', {
     'block': P.TopK(),
     'desc_const': [5],
     'desc_inputs': [[20, 20, 10]],
     'desc_bprop': [[20, 20, 5]],
     'skip': ['backward']}),

Example #4

File: bn_grad_split.py Project: king4arabs/mindspore

# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================

from mindspore.ops import Primitive
from mindspore.ops.operations import _grad_ops as G
from mindspore.ops import _constants as Constants
from mindspore.common.tensor import Tensor
import mindspore.common.dtype as mstype

make_tuple = Primitive('MakeTuple')
tuple_getitem = Primitive(Constants.kTupleGetItem)
bn_grad = G.BatchNormGrad(is_training=True)
sync_bn_grad = G.SyncBatchNormGrad()
bn_grad1 = Primitive('BNGrad1')
bn_grad2 = Primitive('BNGrad2')
bn_grad3 = Primitive('BNGrad3')
bn_training_update_grad = Primitive('BNTrainingUpdateGrad')
bn_training_reduce_grad = Primitive('BNTrainingReduceGrad')
allreduce = Primitive('AllReduce')
mul = Primitive('Mul')
mul_value = Tensor(0.5, mstype.float32)


class FnDict:
    def __init__(self):
        self.fnDict = {}

Example #5

# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================

from mindspore.ops import Primitive
from mindspore.ops.operations import _grad_ops as G

batch_norm_grad = G.BatchNormGrad(is_training=False)
bn_infer_grad = Primitive('BNInferGrad')
make_tuple = Primitive('make_tuple')
tuple_getitem = Primitive('tuple_getitem')


class FnDict:
    def __init__(self):
        self.fnDict = {}

    def __call__(self, fn):
        self.fnDict[fn.__name__] = fn

    def __getitem__(self, name):
        return self.fnDict[name]

Example #6

 ('FusedBatchNormGrad', {
     'block': G.FusedBatchNormGrad(),
     'desc_inputs': [[128, 64, 32, 64], [128, 64, 32, 64], [64], [64],
                     [64]],
     'desc_bprop': [[128, 64, 32, 64], [64], [64], [64], [64]],
     'skip': ['backward']
 }),
 ('BatchNorm', {
     'block': P.BatchNorm(),
     'desc_inputs': [[128, 64, 32, 32], [64], [64], [64], [64]],
     'desc_bprop': [[128, 64, 32, 32], [64], [64], [64], [64]],
     'skip': []
 }),
 ('BatchNormGrad', {
     'block':
     G.BatchNormGrad(),
     'desc_inputs': [[128, 64, 32, 32], [128, 64, 32, 32], [64], [64], [64],
                     [64]],
     'desc_bprop': [[128, 64, 32, 32], [64], [64], [64], [64]],
     'skip': ['backward']
 }),
 ('ApplyMomentum', {
     'block':
     P.ApplyMomentum(),
     'desc_inputs': [[128, 32, 32, 64], [128, 32, 32, 64], [32, 32, 64],
                     [32, 32, 64], [32, 32, 64]],
     'desc_bprop': [[128, 32, 32, 64]],
     'skip': ['backward']
 }),
 ('TopK', {
     'block': P.TopK(),