u99127 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_r374497747
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File path: tests/python/frontend/tflite/test_forward.py
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@@ -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')
Review comment:
I think a testcase is missing to test that out of bounds indices behave as
tflite expects it to behave. See the documentation for relay.op.transform.take
with the last optional parameter for "mode"
See here for more . https://docs.tvm.ai/api/python/relay/op.html
Further, axis is an optional input to gather in tflite and _op.take . Do the
2 semantics match up as I cannot see this obviously in the tflite documentation
?
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