diff --git a/PaddleOCR-VL-0.9B/configuration_paddleocr_vl.py b/PaddleOCR-VL-0.9B/configuration_paddleocr_vl.py deleted file mode 100644 index a8fd139..0000000 --- a/PaddleOCR-VL-0.9B/configuration_paddleocr_vl.py +++ /dev/null @@ -1,191 +0,0 @@ -# Copyright (c) 2025 PaddlePaddle Authors. 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. - -from transformers.configuration_utils import PretrainedConfig -from transformers.modeling_rope_utils import rope_config_validation - -class PaddleOCRVisionConfig(PretrainedConfig): - model_type = "paddleocr_vl" - base_config_key = "vision_config" - - def __init__( - self, - hidden_size=768, - intermediate_size=3072, - num_hidden_layers=12, - num_attention_heads=12, - num_channels=3, - image_size=224, - patch_size=14, - hidden_act="gelu_pytorch_tanh", - layer_norm_eps=1e-6, - attention_dropout=0.0, - spatial_merge_size=2, - temporal_patch_size=2, - tokens_per_second=2, - **kwargs, - ): - super().__init__(**kwargs) - - self.hidden_size = hidden_size - self.intermediate_size = intermediate_size - self.num_hidden_layers = num_hidden_layers - self.num_attention_heads = num_attention_heads - self.num_channels = num_channels - self.patch_size = patch_size - self.image_size = image_size - self.attention_dropout = attention_dropout - self.layer_norm_eps = layer_norm_eps - self.hidden_act = hidden_act - self.spatial_merge_size = spatial_merge_size - self.temporal_patch_size = temporal_patch_size - self.tokens_per_second = tokens_per_second - - - -class PaddleOCRVLConfig(PretrainedConfig): - """ - Configuration class. - - This class stores the configuration of an Ernie model, defining the model architecture. - It inherits from PretrainedConfig and can be used to control model outputs. - """ - - model_type = "paddleocr_vl" - keys_to_ignore_at_inference = ["past_key_values"] - sub_configs = {"vision_config": PaddleOCRVisionConfig} - - # Default tensor parallel plan for base model `Qwen3` - base_model_tp_plan = { - "layers.*.self_attn.q_proj": "colwise", - "layers.*.self_attn.k_proj": "colwise", - "layers.*.self_attn.v_proj": "colwise", - "layers.*.self_attn.o_proj": "rowwise", - "layers.*.mlp.gate_proj": "colwise", - "layers.*.mlp.up_proj": "colwise", - "layers.*.mlp.down_proj": "rowwise", - } - base_model_pp_plan = { - "embed_tokens": (["input_ids"], ["inputs_embeds"]), - "layers": (["hidden_states", "attention_mask"], ["hidden_states"]), - "norm": (["hidden_states"], ["hidden_states"]), - } - - def __init__( - self, - vocab_size=32000, - hidden_size=768, - intermediate_size=11008, - max_position_embeddings=32768, - num_hidden_layers=2, - num_attention_heads=2, - image_token_id=101304, - video_token_id=101305, - vision_start_token_id=101306, - rms_norm_eps=1e-6, - use_cache=False, - use_flash_attention=False, - pad_token_id=0, - bos_token_id=1, - eos_token_id=2, - head_dim=128, - hidden_act="silu", - use_bias=False, - rope_theta=10000, - weight_share_add_bias=True, - ignored_index=-100, - attention_probs_dropout_prob=0.0, - hidden_dropout_prob=0.0, - compression_ratio: float = 1.0, - num_key_value_heads=None, - max_sequence_length=None, - tie_word_embeddings=False, - vision_config=None, - rope_scaling=None, - **kwargs, - ): - """ - Initialize configuration with default or specified parameters. - - Args: - vocab_size (int): Size of the vocabulary (number of unique tokens) - hidden_size (int): Dimensionality of the encoder layers and the pooler layer - intermediate_size (int): Dimensionality of the "intermediate" (feed-forward) layer - max_position_embeddings (int): Maximum sequence length the model can handle - num_hidden_layers (int): Number of hidden layers in the Transformer encoder - num_attention_heads (int): Number of attention heads for each attention layer - rms_norm_eps (float): The epsilon used by the RMS normalization layers - use_cache (bool): Whether to use caching for faster generation (decoding) - use_flash_attention (bool): Whether to use FlashAttention for optimized attention computation - pad_token_id (int): Token ID used for padding sequences - bos_token_id (int): Token ID used for beginning-of-sequence - eos_token_id (int): Token ID used for end-of-sequence - use_bias (bool): Whether to use bias terms in linear layers - rope_theta (float): The base period of the RoPE embeddings - weight_share_add_bias (bool): Whether to share bias weights in certain layers - ignored_index (int): Target value that is ignored during loss computation - attention_probs_dropout_prob (float): Dropout probability for attention weights - hidden_dropout_prob (float): Dropout probability for hidden layers - compression_ratio (float): Ratio for KV cache compression (1.0 = no compression) - num_key_value_heads (int): Number of key/value heads (for Grouped Query Attention) - max_sequence_length (int): Maximum sequence length for positional embeddings - **kwargs: Additional keyword arguments passed to parent class - """ - - # Set default for tied embeddings if not specified. - super().__init__( - pad_token_id=pad_token_id, - bos_token_id=bos_token_id, - eos_token_id=eos_token_id, - **kwargs, - ) - if isinstance(vision_config, dict): - self.vision_config = self.sub_configs["vision_config"](**vision_config) - elif vision_config is None: - self.vision_config = self.sub_configs["vision_config"]() - self.vocab_size = vocab_size - self.hidden_size = hidden_size - self.intermediate_size = intermediate_size - self.max_position_embeddings = max_position_embeddings - self.num_hidden_layers = num_hidden_layers - self.num_attention_heads = num_attention_heads - self.rms_norm_eps = rms_norm_eps - self.use_cache = use_cache - self.use_flash_attention = use_flash_attention - self.pad_token_id = pad_token_id - self.bos_token_id = bos_token_id - self.eos_token_id = eos_token_id - self.image_token_id = image_token_id - self.video_token_id = video_token_id - self.vision_start_token_id = vision_start_token_id - self.head_dim = head_dim - self.hidden_act=hidden_act - self.sliding_window = None - self.hidden_size = hidden_size - self.use_bias = use_bias - self.weight_share_add_bias = weight_share_add_bias - self.rope_theta = rope_theta - self.ignored_index = ignored_index - self.attention_probs_dropout_prob = attention_probs_dropout_prob - self.hidden_dropout_prob = hidden_dropout_prob - self.compression_ratio = compression_ratio - self.num_key_value_heads = num_key_value_heads - self.max_sequence_length = max_sequence_length - self.rope_scaling = rope_scaling - if self.rope_scaling is not None and "type" in self.rope_scaling: - if self.rope_scaling["type"] == "mrope": - self.rope_scaling["type"] = "default" - self.rope_scaling["rope_type"] = self.rope_scaling["type"] - rope_config_validation(self, ignore_keys={"mrope_section"}) - super().__init__(tie_word_embeddings=tie_word_embeddings, **kwargs) \ No newline at end of file