cancel einops
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@ -13,13 +13,6 @@ from .embeddings import get_timestep_embedding
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from .resnet import Upsample
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from .resnet import Upsample
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# try:
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# from einops import rearrange, repeat
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# except:
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# print("Einops is not installed")
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# pass
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def exists(val):
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def exists(val):
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return val is not None
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return val is not None
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@ -17,7 +17,6 @@ from ..modeling_utils import ModelMixin
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# pass
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# pass
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class SinusoidalPosEmb(nn.Module):
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class SinusoidalPosEmb(nn.Module):
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def __init__(self, dim):
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def __init__(self, dim):
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super().__init__()
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super().__init__()
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@ -11,11 +11,11 @@
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# limitations under the License.
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from typing import Union
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import numpy as np
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import numpy as np
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import torch
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import torch
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from typing import Union
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SCHEDULER_CONFIG_NAME = "scheduler_config.json"
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SCHEDULER_CONFIG_NAME = "scheduler_config.json"
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@ -53,11 +53,7 @@ class SchedulerMixin:
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raise ValueError(f"`self.tensor_format`: {self.tensor_format} is not valid.")
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raise ValueError(f"`self.tensor_format`: {self.tensor_format} is not valid.")
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def match_shape(
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def match_shape(self, values: Union[np.ndarray, torch.Tensor], broadcast_array: Union[np.ndarray, torch.Tensor]):
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self,
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values: Union[np.ndarray, torch.Tensor],
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broadcast_array: Union[np.ndarray, torch.Tensor]
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):
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"""
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"""
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Turns a 1-D array into an array or tensor with len(broadcast_array.shape) dims.
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Turns a 1-D array into an array or tensor with len(broadcast_array.shape) dims.
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@ -21,7 +21,8 @@ import unittest
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import numpy as np
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import numpy as np
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import torch
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import torch
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from diffusers import ( # GradTTSPipeline,
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from diffusers import (
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GradTTSPipeline,
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BDDMPipeline,
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BDDMPipeline,
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DDIMPipeline,
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DDIMPipeline,
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DDIMScheduler,
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DDIMScheduler,
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