docstr: Test computation with 'same' padding and no output padding
docstr_tok: ["Test","computation","with","'same","'","padding","and","no","output","padding"]
code: def test_same_padding_without_output_padding(self):
      """Test computation with 'same' padding and no output padding"""
      (
          torch_paddings,
          torch_output_paddings,
      ) = compute_conv_transpose_padding_args_for_torch(
          input_shape=(1, 5, 5, 3),
          kernel_shape=(3, 3, 3, 3),
          strides=2,
          padding="same",
          output_padding=None,
          dilation_rate=1,
      )
      self.assertEqual(torch_paddings, [1, 1])
      self.assertEqual(torch_output_paddings, [1, 1])
  
imports: from keras.backend.common.backend_utils import _convert_conv_tranpose_padding_args_from_keras_to_jax
  from keras.backend.common.backend_utils import _convert_conv_tranpose_padding_args_from_keras_to_torch
  from keras.backend.common.backend_utils import _get_output_shape_given_tf_padding
  from keras.backend.common.backend_utils import compute_conv_transpose_padding_args_for_jax
  from keras.backend.common.backend_utils import compute_conv_transpose_padding_args_for_torch
  from keras.testing import test_case
label_desc: Use image node_id 2 for calling the ComputeConvTransposePaddingArgsForTorchTest obj's underlying member method code with example usage: obj.test_same_padding_without_output_padding() without return types