Merge branch 'mindspore-lab:master' into master

Author: Tridu33

mindnlp/peft_lora_mindnlp.ipynb

@@ -152,6 +152,7 @@
     mobilenet_v1,
     mobilenet_v2,
     mobilevit,
+    mobilevitv2,
     mpnet,
     mpt,
     mllama,
@@ -395,6 +396,7 @@
 from .mobilenet_v1 import *
 from .mobilenet_v2 import *
 from .mobilevit import *
+from .mobilevitv2 import *
 from .mpnet import *
 from .mllama import *
 from .mluke import *
@@ -640,6 +642,7 @@
 __all__.extend(mobilenet_v1.__all__)
 __all__.extend(mobilenet_v2.__all__)
 __all__.extend(mobilevit.__all__)
+__all__.extend(mobilevitv2.__all__)
 __all__.extend(mpnet.__all__)
 __all__.extend(mpt.__all__)
 __all__.extend(mt5.__all__)

mindnlp/peft_lora_pytorch.ipynb

@@ -0,0 +1,30 @@
+# Copyright 2024 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================
+"""
+MobileVit Model init
+"""
+from . import configuration_mobilevitv2, modeling_mobilevitv2
+from ..mobilevit import feature_extraction_mobilevit, image_processing_mobilevit
+
+from .configuration_mobilevitv2 import *
+from ..mobilevit.feature_extraction_mobilevit import *
+from ..mobilevit.image_processing_mobilevit import *
+from .modeling_mobilevitv2 import *
+
+__all__ = []
+__all__.extend(configuration_mobilevitv2.__all__)
+__all__.extend(feature_extraction_mobilevit.__all__)
+__all__.extend(image_processing_mobilevit.__all__)
+__all__.extend(modeling_mobilevitv2.__all__)

mindnlp/transformers/models/__init__.py

@@ -0,0 +1,145 @@
+# coding=utf-8
+# Copyright 2023 The HuggingFace Inc. team. 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.
+"""MobileViTV2 model configuration"""
+
+
+from ...configuration_utils import PretrainedConfig
+
+from ....utils import logging
+
+
+logger = logging.get_logger(__name__)
+
+
+class MobileViTV2Config(PretrainedConfig):
+    r"""
+    This is the configuration class to store the configuration of a [`MobileViTV2Model`]. It is used to instantiate a
+    MobileViTV2 model according to the specified arguments, defining the model architecture. Instantiating a
+    configuration with the defaults will yield a similar configuration to that of the MobileViTV2
+    [apple/mobilevitv2-1.0](https://huggingface.co/apple/mobilevitv2-1.0) architecture.
+
+    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
+    documentation from [`PretrainedConfig`] for more information.
+
+    Args:
+        num_channels (`int`, *optional*, defaults to 3):
+            The number of input channels.
+        image_size (`int`, *optional*, defaults to 256):
+            The size (resolution) of each image.
+        patch_size (`int`, *optional*, defaults to 2):
+            The size (resolution) of each patch.
+        expand_ratio (`float`, *optional*, defaults to 2.0):
+            Expansion factor for the MobileNetv2 layers.
+        hidden_act (`str` or `function`, *optional*, defaults to `"swish"`):
+            The non-linear activation function (function or string) in the Transformer encoder and convolution layers.
+        conv_kernel_size (`int`, *optional*, defaults to 3):
+            The size of the convolutional kernel in the MobileViTV2 layer.
+        output_stride (`int`, *optional*, defaults to 32):
+            The ratio of the spatial resolution of the output to the resolution of the input image.
+        classifier_dropout_prob (`float`, *optional*, defaults to 0.1):
+            The dropout ratio for attached classifiers.
+        initializer_range (`float`, *optional*, defaults to 0.02):
+            The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
+        layer_norm_eps (`float`, *optional*, defaults to 1e-05):
+            The epsilon used by the layer normalization layers.
+        aspp_out_channels (`int`, *optional*, defaults to 512):
+            Number of output channels used in the ASPP layer for semantic segmentation.
+        atrous_rates (`List[int]`, *optional*, defaults to `[6, 12, 18]`):
+            Dilation (atrous) factors used in the ASPP layer for semantic segmentation.
+        aspp_dropout_prob (`float`, *optional*, defaults to 0.1):
+            The dropout ratio for the ASPP layer for semantic segmentation.
+        semantic_loss_ignore_index (`int`, *optional*, defaults to 255):
+            The index that is ignored by the loss function of the semantic segmentation model.
+        n_attn_blocks (`List[int]`, *optional*, defaults to `[2, 4, 3]`):
+            The number of attention blocks in each MobileViTV2Layer
+        base_attn_unit_dims (`List[int]`, *optional*, defaults to `[128, 192, 256]`):
+            The base multiplier for dimensions of attention blocks in each MobileViTV2Layer
+        width_multiplier (`float`, *optional*, defaults to 1.0):
+            The width multiplier for MobileViTV2.
+        ffn_multiplier (`int`, *optional*, defaults to 2):
+            The FFN multiplier for MobileViTV2.
+        attn_dropout (`float`, *optional*, defaults to 0.0):
+            The dropout in the attention layer.
+        ffn_dropout (`float`, *optional*, defaults to 0.0):
+            The dropout between FFN layers.
+
+    Example:
+
+    ```python
+    >>> from transformers import MobileViTV2Config, MobileViTV2Model
+
+    >>> # Initializing a mobilevitv2-small style configuration
+    >>> configuration = MobileViTV2Config()
+
+    >>> # Initializing a model from the mobilevitv2-small style configuration
+    >>> model = MobileViTV2Model(configuration)
+
+    >>> # Accessing the model configuration
+    >>> configuration = model.config
+    ```"""
+
+    model_type = "mobilevitv2"
+
+    def __init__(
+        self,
+        num_channels=3,
+        image_size=256,
+        patch_size=2,
+        expand_ratio=2.0,
+        hidden_act="swish",
+        conv_kernel_size=3,
+        output_stride=32,
+        classifier_dropout_prob=0.1,
+        initializer_range=0.02,
+        layer_norm_eps=1e-5,
+        aspp_out_channels=512,
+        atrous_rates=[6, 12, 18],
+        aspp_dropout_prob=0.1,
+        semantic_loss_ignore_index=255,
+        n_attn_blocks=[2, 4, 3],
+        base_attn_unit_dims=[128, 192, 256],
+        width_multiplier=1.0,
+        ffn_multiplier=2,
+        attn_dropout=0.0,
+        ffn_dropout=0.0,
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+
+        self.num_channels = num_channels
+        self.image_size = image_size
+        self.patch_size = patch_size
+        self.expand_ratio = expand_ratio
+        self.hidden_act = hidden_act
+        self.conv_kernel_size = conv_kernel_size
+        self.output_stride = output_stride
+        self.initializer_range = initializer_range
+        self.layer_norm_eps = layer_norm_eps
+        self.n_attn_blocks = n_attn_blocks
+        self.base_attn_unit_dims = base_attn_unit_dims
+        self.width_multiplier = width_multiplier
+        self.ffn_multiplier = ffn_multiplier
+        self.ffn_dropout = ffn_dropout
+        self.attn_dropout = attn_dropout
+        self.classifier_dropout_prob = classifier_dropout_prob
+
+        # decode head attributes for semantic segmentation
+        self.aspp_out_channels = aspp_out_channels
+        self.atrous_rates = atrous_rates
+        self.aspp_dropout_prob = aspp_dropout_prob
+        self.semantic_loss_ignore_index = semantic_loss_ignore_index
+
+
+__all__=['MobileViTV2Config']