Add phi-3 model support for pipeline parallel inference

python/llm/example/GPU/Pipeline-Parallel-Inference/README.md

@@ -13,6 +13,9 @@ To run this example with IPEX-LLM on Intel GPUs, we have some recommended requir
 - [Qwen/Qwen1.5-14B-Chat](./run_qwen1.5_arc_2_card.sh)
 - [baichuan-inc/Baichuan2-7B-Chat](./run_baichuan2_arc_2_card.sh)
 - [baichuan-inc/Baichuan2-13B-Chat](./run_baichuan2_arc_2_card.sh)
+- [microsoft/Phi-3-mini-4k-instruct](./run_phi3_arc_2_card.sh)
+- [microsoft/Phi-3-medium-4k-instruct](./run_phi3_arc_2_card.sh)
+
 
 ## Example: Run pipeline parallel inference on multiple GPUs
 
@@ -81,6 +84,22 @@ bash run_baichuan2_arc_2_card.sh
 
 </details>
 
+</details>
+
+<details>
+  <summary> Show Phi3 example </summary>
+
+#### Run Phi-3-mini-4k-instruct / Phi-3-medium-4k-instruct on two Intel Arc A770
+
+You could specify `--repo-id-or-model-path` in the test script to be the huggingface repo id for Phi3 to be downloaded, or the path to the huggingface checkpoint folder. Besides, you could change `NUM_GPUS` to the number of GPUs you have on your machine.
+
+```bash
+pip install transformers==4.37.0
+bash run_phi3_arc_2_card.sh
+```
+
+</details>
+
 ### 3. Sample Output
 #### [meta-llama/Llama-2-13b-chat-hf](https://huggingface.co/meta-llama/Llama-2-13b-chat-hf)
 ```log

python/llm/example/GPU/Pipeline-Parallel-Inference/run_phi3_arc_2_card.sh

@@ -0,0 +1,37 @@
+#
+# Copyright 2016 The BigDL Authors.
+#
+# 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.
+#
+
+source /opt/intel/oneapi/setvars.sh
+export MASTER_ADDR=127.0.0.1
+export MASTER_PORT=9090
+export FI_PROVIDER=tcp
+export USE_XETLA=OFF
+export OMP_NUM_THREADS=6
+export IPEX_LLM_QUANTIZE_KV_CACHE=1
+if [[ $KERNEL_VERSION != *"6.5"* ]]; then
+    export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
+fi
+export TORCH_LLM_ALLREDUCE=0
+
+NUM_GPUS=2 # number of used GPU
+
+# To run Phi-3-medium-4k-instruct
+CCL_ZE_IPC_EXCHANGE=sockets torchrun --standalone --nnodes=1 --nproc-per-node $NUM_GPUS \
+    generate.py --repo-id-or-model-path 'microsoft/Phi-3-medium-4k-instruct' --gpu-num $NUM_GPUS
+
+# # To run Phi-3-mini-4k-instruct
+# CCL_ZE_IPC_EXCHANGE=sockets torchrun --standalone --nnodes=1 --nproc-per-node $NUM_GPUS \
+#     generate.py --repo-id-or-model-path 'microsoft/Phi-3-mini-4k-instruct' --gpu-num $NUM_GPUS

python/llm/src/ipex_llm/transformers/models/phi3.py

@@ -234,7 +234,8 @@ def model_forward(
     ):
         # IPEX-LLM OPT: kv cache and quantize kv cache and sdp
         use_cache = use_cache if use_cache is not None else self.config.use_cache
-        use_quantize_kv = use_quantize_kv_cache(self.layers[0].mlp.down_proj, input_ids)
+        input = input_ids if input_ids is not None else inputs_embeds
+        use_quantize_kv = use_quantize_kv_cache(self.layers[0].mlp.down_proj, input)
         if use_cache:
             if use_quantize_kv and not isinstance(past_key_values, DynamicFp8Cache):
                 past_key_values = DynamicFp8Cache.from_legacy_cache(past_key_values)

python/llm/src/ipex_llm/transformers/pipeline_parallel.py

@@ -48,6 +48,7 @@ def __init__(self, *args):
         # to avoid AttributeError in https://github.com/intel-analytics/ipex-llm/blob/main/
         # python/llm/src/ipex_llm/transformers/models/llama.py#L119
         self.up_proj = DummyLayer()
+        self.down_proj = DummyLayer()
 
     def forward(self, x):
         return x