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""" - def __init__(self): + def __init__(self, dim: int, output_dim: int): super(Model, self).__init__() + self.weight = nn.Parameter(torch.randn(dim, output_dim)) def forward(self, x: torch.Tensor) -> torch.Tensor: """ - Applies ReLU activation to the input tensor. + Performs matrix multiplication followed by ReLU activation. Args: - x (torch.Tensor): Input tensor of any shape. + x (torch.Tensor): Input tensor of shape (batch_size, input_dim). Returns: - torch.Tensor: Output tensor with ReLU applied, same shape as input. + torch.Tensor: Output tensor with shape (batch_size, output_dim), with ReLU applied after matrix multiplication. """ + # Perform matrix multiplication + x = torch.matmul(x, self.weight) + # Apply ReLU activation return torch.relu(x) batch_size = 16 dim = 16384 +output_dim = 1024 def get_inputs(): x = torch.randn(batch_size, dim) -- Gitee From 305966e50cb920f7f1418b9d3709461aa7798151 Mon Sep 17 00:00:00 2001 From: sunjiachen111 <1720638369@qq.com> Date: Thu, 11 Sep 2025 16:00:05 +0800 Subject: [PATCH 2/2] 111 --- example/001-example/prompt.txt | 4 ++++ example/001-example/run_code.py | 4 +++- 2 files changed, 7 insertions(+), 1 deletion(-) diff --git a/example/001-example/prompt.txt b/example/001-example/prompt.txt index 2fecbf3..34123f2 100644 --- a/example/001-example/prompt.txt +++ b/example/001-example/prompt.txt @@ -56,6 +56,10 @@ def get_init_inputs(): # randomly generate tensors required for initialization based on the model architecture return [] ``` + + + + You are given the following architecture: diff --git a/example/001-example/run_code.py b/example/001-example/run_code.py index a18a7cd..035c9d6 100644 --- a/example/001-example/run_code.py +++ b/example/001-example/run_code.py @@ -7,6 +7,8 @@ import time from example_torchcode import Model,get_inputs,get_init_inputs from example_cudacode import ModelNew + + def run_benchmark(): # 检查 CUDA 是否可用 if not torch.cuda.is_available(): @@ -43,7 +45,7 @@ def run_benchmark(): print("❌ 精度不一致！") print("\n-------------------- 性能加速比测试 --------------------") - num_iterations = 100 + num_iterations = 1000 # PyTorch 模型计时 torch.cuda.synchronize() -- Gitee