"""调试 TensorRT 输出 shape"""
import sys
import os
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

import numpy as np

try:
    import tensorrt as trt
    import pycuda.driver as cuda
    import pycuda.autoinit
    
    engine_path = "./models/yolo11n.engine"
    
    with open(engine_path, "rb") as f:
        runtime = trt.Runtime(trt.Logger(trt.Logger.WARNING))
        engine = runtime.deserialize_cuda_engine(f.read())
    
    context = engine.create_execution_context()
    
    input_shape = (1, 3, 480, 480)
    input_data = np.random.randn(*input_shape).astype(np.float32)
    
    input_binding_idx = 0
    output_binding_idx = 1
    
    output_shape = engine.get_binding_shape(output_binding_idx)
    print(f"Engine 定义 output shape: {output_shape}")
    
    context.set_input_shape(engine.get_binding_name(0), input_shape)
    
    output_size = int(np.prod([max(1, s) for s in output_shape]))
    
    h_input = cuda.pagelocked_empty(input_data.size, np.float32)
    h_output = cuda.pagelocked_empty(output_size, np.float32)
    
    np.copyto(h_input, input_data.ravel())
    
    d_input = cuda.mem_alloc(h_input.nbytes)
    d_output = cuda.mem_alloc(h_output.nbytes)
    
    bindings = [int(d_input), int(d_output)]
    
    cuda.memcpy_htod(d_input, h_input)
    context.execute_v2(bindings=bindings)
    cuda.memcpy_dtoh(h_output, d_output)
    
    output_array = h_output.reshape(output_shape)
    
    print(f"\n实际输出:")
    print(f"  dtype: {output_array.dtype}")
    print(f"  shape: {output_array.shape}")
    print(f"  ndim: {output_array.ndim}")
    
    if output_array.ndim == 1:
        print(f"  total elements: {output_array.shape[0]}")
        print(f"  expected (84*4725): {84 * 4725}")
    elif output_array.ndim == 2:
        print(f"  shape[0]: {output_array.shape[0]} (detections)")
        print(f"  shape[1]: {output_array.shape[1]} (features)")
    elif output_array.ndim == 3:
        print(f"  shape[0]: {output_array.shape[0]} (batch)")
        print(f"  shape[1]: {output_array.shape[1]} (classes+coords)")
        print(f"  shape[2]: {output_array.shape[2]} (num_boxes)")
    
except Exception as e:
    print(f"Error: {e}")
    import traceback
    traceback.print_exc()