output to 1d

[Moonmore]

I'm new to TensorRT and am using the ONNX-TensorRT project to build inference engine, but I've encountered some issues during implementation: When running the following demo code, I notice that the output shape consistently differs from my expectations, always producing a 1-d shape [32*1280]. I've identified code supporting dynamic dimensions in the ONNX-TensorRT source. My question is: do these outputs require manual reshaping, or is there an issue with the code that I haven't identified? I greatly appreciate your response

version
tensorRT：10.2
onnx-tensort：10.14
torch: 1.16

import torch 
import onnx
import onnxruntime
import onnx_tensort.backend as backend
import numpy as np

class Model(torch.nn.Module):
    def __init__(self):
        super(Model, self).__init__()
        self.linear = torch.nn.Linear(1280, 1280)
    def forward(self, embed_x):
        concat_hidden_state = self.linear(embed_x)
        return concat_hidden_state
    
embed_x = torch.ones((1, 10, 1280), dtype=torch.float32)
model = Model()

torch.onnx.export(
    model,
    (embed_x),
    "./model.onnx",
    input_names=["embed_x"],
    output_names=["concat_hidden_state"]
    dynamic_axes={
        "embed_x": {1: "embed_x_len"},
        "concat_hidden_state": {1:"concat_len"}
    }
)

onnx_model = onnx.load("./model.onnx")
engine = backend.prepare(onnx_model, device="CUDA:1")

x = np.random.rand(1, 32, 1280).astype(np.float32)
all_output = engine.run(x)

for out in all_output:
    print(out.shape)
model = Model()

torch.onnx.export(
    model,
    (embed_x),
    "./model.onnx",
    input_names=["embed_x"],
    output_names=["concat_hidden_state"]
    dynamic_axes={
        "embed_x": {1: "embed_x_len"},
        "concat_hidden_state": {1:"concat_len"}
    }
)

onnx_model = onnx.load("./model.onnx")
engine = backend.prepare(onnx_model, device="CUDA:1")

x = np.random.rand(1, 32, 1280).astype(np.float32)
all_output = engine.run(x)

for out in all_output:
    print(out.shape)