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09d8e80 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 | # Copyright 2019 DeepMind Technologies Limited. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# 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.
# ==============================================================================
"""The transforms sub-package."""
from optax.transforms._accumulation import ema
from optax.transforms._accumulation import EmaState
from optax.transforms._accumulation import MultiSteps
from optax.transforms._accumulation import MultiStepsState
from optax.transforms._accumulation import ShouldSkipUpdateFunction
from optax.transforms._accumulation import skip_large_updates
from optax.transforms._accumulation import skip_not_finite
from optax.transforms._accumulation import trace
from optax.transforms._accumulation import TraceState
from optax.transforms._adding import add_decayed_weights
from optax.transforms._adding import add_noise
from optax.transforms._adding import AddNoiseState
from optax.transforms._clipping import adaptive_grad_clip
from optax.transforms._clipping import clip
from optax.transforms._clipping import clip_by_block_rms
from optax.transforms._clipping import clip_by_global_norm
from optax.transforms._clipping import per_example_global_norm_clip
from optax.transforms._clipping import per_example_layer_norm_clip
from optax.transforms._clipping import unitwise_clip
from optax.transforms._clipping import unitwise_norm
from optax.transforms._combining import chain
from optax.transforms._combining import named_chain
from optax.transforms._combining import partition
from optax.transforms._combining import PartitionState
from optax.transforms._conditionality import apply_if_finite
from optax.transforms._conditionality import ApplyIfFiniteState
from optax.transforms._conditionality import conditionally_mask
from optax.transforms._conditionality import conditionally_transform
from optax.transforms._conditionality import ConditionallyMaskState
from optax.transforms._conditionality import ConditionallyTransformState
from optax.transforms._conditionality import ConditionFn
from optax.transforms._constraining import keep_params_nonnegative
from optax.transforms._constraining import NonNegativeParamsState
from optax.transforms._constraining import zero_nans
from optax.transforms._constraining import ZeroNansState
from optax.transforms._layouts import flatten
from optax.transforms._masking import masked
from optax.transforms._masking import MaskedNode
from optax.transforms._masking import MaskedState
__all__ = (
"adaptive_grad_clip",
"add_decayed_weights",
"add_noise",
"AddNoiseState",
"apply_if_finite",
"ApplyIfFiniteState",
"chain",
"clip_by_block_rms",
"clip_by_global_norm",
"clip",
"conditionally_mask",
"ConditionallyMaskState",
"conditionally_transform",
"ConditionallyTransformState",
"ema",
"EmaState",
"flatten",
"keep_params_nonnegative",
"masked",
"MaskedState",
"MultiSteps",
"MultiStepsState",
"named_chain",
"NonNegativeParamsState",
"partition",
"PartitionState",
"ShouldSkipUpdateFunction",
"skip_large_updates",
"skip_not_finite",
"trace",
"TraceState",
"zero_nans",
"ZeroNansState",
)
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