siju-samuel commented on a change in pull request #4788: [FRONTEND][TFLITE]Gather, StridedSlice op support added URL: https://github.com/apache/incubator-tvm/pull/4788#discussion_r379762709
########## File path: tests/python/frontend/tflite/test_forward.py ########## @@ -244,6 +244,74 @@ def test_forward_slice(): _test_slice(np.arange(8, dtype=np.int32).reshape((2, 4)), begin=[0, 1], size=[-1, -1]) _test_slice(np.arange(5, dtype=np.int32).reshape((5, )), begin=[4], size=[-1]) +####################################################################### +# Gather +# ------ + +def _test_gather(dshape, indices, axis, dtype): + """ One iteration of Gather """ + data = np.random.uniform(1, 10, size=dshape).astype(dtype) + indices = np.asarray(indices).astype('int32') + + with tf.Graph().as_default(): + in_data = array_ops.placeholder(shape=data.shape, dtype=data.dtype) + out = array_ops.gather(in_data, indices, axis=axis) + compare_tflite_with_tvm(data, 'Placeholder:0', [in_data], [out]) + + #Test quantized input + data = np.random.uniform(1, 10, size=dshape).astype(np.uint8) + with tf.Graph().as_default(): + in_data = array_ops.placeholder(shape=data.shape, dtype=data.dtype, name="in_data") + out = array_ops.gather(in_data, indices, axis=axis) + compare_tflite_with_tvm([data], ['in_data:0'], [in_data], [out], quantized=True) + +def test_forward_gather(): + """ GATHER """ + _test_gather((4,), [1], 0, 'float32') + _test_gather((1, 4), [0], 0, 'int32') + _test_gather((4,), [[[1, 0], [0, 1]]], 0, 'float32') + _test_gather((2, 2), [[[1, 0], [0, 1]]], 0, 'int32') + _test_gather((2, 2), [[[1, 0], [0, 1]]], 1, 'int32') + _test_gather((2, 2), [[[1, 0], [0, 1]]], 0, 'float32') + _test_gather((3, 3, 3), [[[1, 0]]], 0, 'int32') + _test_gather((3, 3, 3), [[[1, 0]]], 2, 'int32') + _test_gather((4, 3, 5, 6), [[2, 1, 0, 0]], 0, 'float32') + +####################################################################### +# StridedSlice +# ------------ + +def _test_stridedslice(ip_shape, begin, end, stride, dtype, + begin_mask=0, end_mask=0, new_axis_mask=0, + shrink_axis_mask=0, ellipsis_mask=0): + """ One iteration of a Stridedslice """ + data = np.random.uniform(size=ip_shape).astype(dtype) + with tf.Graph().as_default(): + in_data = tf.placeholder(dtype, ip_shape, name="in_data") + out = array_ops.strided_slice(in_data, begin, end, stride, + begin_mask=begin_mask, + end_mask=end_mask, new_axis_mask=new_axis_mask, + shrink_axis_mask=shrink_axis_mask, + ellipsis_mask=ellipsis_mask) + compare_tflite_with_tvm(data, 'in_data:0', [in_data], [out]) + + #Test with quantized inputs + data = np.random.uniform(size=ip_shape).astype(np.uint8) + with tf.Graph().as_default(): + in_data = tf.placeholder(dtype, ip_shape, name="in_data") + out = array_ops.strided_slice(in_data, begin, end, stride, + begin_mask=begin_mask, + end_mask=end_mask, new_axis_mask=new_axis_mask, + shrink_axis_mask=shrink_axis_mask, + ellipsis_mask=ellipsis_mask) + compare_tflite_with_tvm([data], ['in_data:0'], [in_data], [out], quantized=True) + +def test_forward_stridedslice(): + '''test StridedSlice''' Review comment: Even though tf2.0 supports begin_mask, end_mask, ellipsis_mask, new_axis_mask and shrink_axis_mask, tflite doesn't support these and expect these values to be zero. So we donot need to import all cases from tensorflow testcases. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services