chore: import upstream snapshot with attribution

2026-07-13 13:18:33 +08:00
commit 4ececc111a
2017 changed files with 331736 additions and 0 deletions
@@ -0,0 +1,91 @@
+# Copyright (c) Microsoft Corporation.
+# SPDX-License-Identifier: Apache-2.0
+
+# DeepSpeed Team
+
+# Create a container object to save model-specific tensors using the policy file above.
+
+from ..common_parameters import *
+from ..layer_container_base import LayerContainer
+'''
+ # HF Phi-2 model looks like this:
+
+PhiForCausalLM(
+  (model): PhiModel(
+    (embed_tokens): Embedding(51200, 2560)
+    (embed_dropout): Dropout(p=0.0, inplace=False)
+    (layers): ModuleList(
+      (0-31): 32 x PhiDecoderLayer(
+        (self_attn): PhiAttention(
+          (q_proj): Linear(in_features=2560, out_features=2560, bias=True)
+          (k_proj): Linear(in_features=2560, out_features=2560, bias=True)
+          (v_proj): Linear(in_features=2560, out_features=2560, bias=True)
+          (dense): Linear(in_features=2560, out_features=2560, bias=True)
+          (rotary_emb): PhiRotaryEmbedding()
+        )
+        (mlp): PhiMLP(
+          (activation_fn): NewGELUActivation()
+          (fc1): Linear(in_features=2560, out_features=10240, bias=True)
+          (fc2): Linear(in_features=10240, out_features=2560, bias=True)
+        )
+        (input_layernorm): LayerNorm((2560,), eps=1e-05, elementwise_affine=True)
+        (resid_dropout): Dropout(p=0.1, inplace=False)
+      )
+    )
+    (final_layernorm): LayerNorm((2560,), eps=1e-05, elementwise_affine=True)
+  )
+  (lm_head): Linear(in_features=2560, out_features=51200, bias=True)
+)
+'''
+
+
+class PhiTransformerContainer(LayerContainer):
+    """
+        Transformer layer container for the Phi model.
+    """
+    qkv_w: UnfusedQKVParameter
+    qkv_b: UnfusedQKVParameter
+    attn_out_w: AttentionOutputParameter
+    attn_out_b: AttentionOutputParameter
+    mlp_1_w: MLP1Parameter
+    mlp_1_b: MLP1Parameter
+    mlp_2_w: MLP2Parameter
+    mlp_2_b: MLP2Parameter
+    ln_gamma: NormParameter
+    ln_beta: NormParameter
+
+    PARAM_MAPPING = {
+        "self_attn.q_proj.weight": "qkv_w.q_params",
+        "self_attn.k_proj.weight": "qkv_w.k_params",
+        "self_attn.v_proj.weight": "qkv_w.v_params",
+        "self_attn.q_proj.bias": "qkv_b.q_params",
+        "self_attn.k_proj.bias": "qkv_b.k_params",
+        "self_attn.v_proj.bias": "qkv_b.v_params",
+        "self_attn.dense.weight": "attn_out_w.params",
+        "self_attn.dense.bias": "attn_out_b.params",
+        "mlp.fc1.weight": "mlp_1_w.params",
+        "mlp.fc1.bias": "mlp_1_b.params",
+        "mlp.fc2.weight": "mlp_2_w.params",
+        "mlp.fc2.bias": "mlp_2_b.params",
+        "input_layernorm.weight": "ln_gamma.params",
+        "input_layernorm.bias": "ln_beta.params",
+    }
+
+
+class PhiNonTransformerContainer(LayerContainer):
+    """
+        Non-Transformer layer container for the Phi model.
+    """
+    word_emb: EmbeddingParameter
+    word_unembed_w: UnembedParameter
+    word_unembed_b: UnembedParameter
+    final_norm_gamma: NormParameter
+    final_norm_beta: NormParameter
+
+    PARAM_MAPPING = {
+        "model.embed_tokens.weight": "word_emb.params",
+        "model.final_layernorm.weight": "final_norm_gamma.params",
+        "model.final_layernorm.bias": "final_norm_beta.params",
+        "lm_head.weight": "word_unembed_w.params",
+        "lm_head.bias": "word_unembed_b.params",
+    }