code: def is_same_padding(padding, stride, kernel_size, input_shape):
      output_shape = tuple(
          (input_shape[i] + 2 * padding[i] - kernel_size[i])
          // stride[i]
          + 1
          for i in range(len(padding))
      )
      return all(
          output_shape[i] == math.ceil(input_shape[i] / stride[i])
          for i in range(len(padding))
      )
  
file_path: ivy/ivy_tests/test_ivy/test_frontends/test_torch/test_nn/test_functional/test_pooling_functions.py
imports: from hypothesis import strategies
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_test
  import math
label_desc: Use image node_id 2 for calling a global function with example usage: is_same_padding(padding, stride, kernel_size, input_shape) and returns: all