[bug-fix] Make resnet barracuda-compatible (#5358)

ml-agents/mlagents/trainers/torch/encoders.py

                 layers.append(ResNetBlock(channel))
             last_channel = channel
         layers.append(Swish())
+        self.final_flat_size = n_channels[-1] * height * width
-            n_channels[-1] * height * width,
+            self.final_flat_size,
             output_size,
             kernel_init=Initialization.KaimingHeNormal,
             kernel_gain=1.41,  # Use ReLU gain
     def forward(self, visual_obs: torch.Tensor) -> torch.Tensor:
         if not exporting_to_onnx.is_exporting():
             visual_obs = visual_obs.permute([0, 3, 1, 2])
-        batch_size = visual_obs.shape[0]
-        before_out = hidden.reshape(batch_size, -1)
+        before_out = hidden.reshape(-1, self.final_flat_size)
         return torch.relu(self.dense(before_out))