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new 2ee860e [TFLite] Cast operator adapted for MLIR-based convertor
(#7639)
2ee860e is described below
commit 2ee860e902e77f45996a5585fc09c5e5c29788e1
Author: Dmitriy Smirnov <[email protected]>
AuthorDate: Fri Mar 19 06:47:45 2021 +0000
[TFLite] Cast operator adapted for MLIR-based convertor (#7639)
* [TFLite] Cast operator adapted for MLIR-based convertor
Cast operator now can be executed in MLIR-based version.
Unit test updated
Change-Id: I30e5c1c9d69355116b560af8f6d0582b2d593538
* Comment added
Change-Id: I3e2d29ef201283de337168d0b82679b63ca2fcf4
---
python/tvm/relay/frontend/tflite.py | 17 ++++++++++++-----
tests/python/frontend/tflite/test_forward.py | 19 ++++++++++++++-----
2 files changed, 26 insertions(+), 10 deletions(-)
diff --git a/python/tvm/relay/frontend/tflite.py
b/python/tvm/relay/frontend/tflite.py
index d6f7047..a5c9a58 100644
--- a/python/tvm/relay/frontend/tflite.py
+++ b/python/tvm/relay/frontend/tflite.py
@@ -2336,11 +2336,18 @@ class OperatorConverter(object):
input_tensor = input_tensors[0]
in_expr = self.get_expr(input_tensor.tensor_idx)
- assert op.BuiltinOptionsType() == BuiltinOptions.CastOptions
- op_options = op.BuiltinOptions()
- cast_options = CastOptions()
- cast_options.Init(op_options.Bytes, op_options.Pos)
- cast_dtype = cast_options.OutDataType()
+ # MLIR-based converter outputs no BuiltinOptions for Cast operator. In
this
+ # case the output type can be derived from the Cast operator output
tensor.
+ # When TOCO converter is used there will be "normal"
BuiltinOptions.CastOptions
+ # with output type.
+ if op.BuiltinOptions() is not None:
+ assert op.BuiltinOptionsType() == BuiltinOptions.CastOptions
+ op_options = op.BuiltinOptions()
+ cast_options = CastOptions()
+ cast_options.Init(op_options.Bytes, op_options.Pos)
+ cast_dtype = cast_options.OutDataType()
+ else:
+ cast_dtype = self.get_output_tensors(op)[0].tensor.Type()
out = _op.cast(in_expr, self.get_tensor_type_str(cast_dtype))
diff --git a/tests/python/frontend/tflite/test_forward.py
b/tests/python/frontend/tflite/test_forward.py
index 0d02c15..7c12cd3 100644
--- a/tests/python/frontend/tflite/test_forward.py
+++ b/tests/python/frontend/tflite/test_forward.py
@@ -647,19 +647,28 @@ def test_forward_transpose():
# ----
-def _test_cast(data, cast_dtype):
+def _test_cast(data, cast_dtype, use_mlir=False):
""" One iteration of CAST """
with tf.Graph().as_default():
in_data = array_ops.placeholder(shape=data.shape, dtype=data.dtype)
out = math_ops.cast(in_data, cast_dtype)
- compare_tflite_with_tvm(data, "Placeholder:0", [in_data], [out])
+ compare_tflite_with_tvm(
+ data, "Placeholder:0", [in_data], [out],
experimental_new_converter=use_mlir
+ )
def test_forward_cast():
""" CAST """
- _test_cast(np.arange(6.0, dtype=np.float32).reshape((1, 6)),
cast_dtype=tf.int32)
- _test_cast(np.arange(6.0, dtype=np.float32).reshape((1, 6)),
cast_dtype=tf.uint8)
- _test_cast(np.arange(6.0, dtype=np.int32).reshape((1, 6)),
cast_dtype=tf.int64)
+ for use_mlir in [False, True]:
+ _test_cast(
+ np.arange(6.0, dtype=np.float32).reshape((1, 6)),
cast_dtype=tf.int32, use_mlir=use_mlir
+ )
+ _test_cast(
+ np.arange(6.0, dtype=np.float32).reshape((1, 6)),
cast_dtype=tf.uint8, use_mlir=use_mlir
+ )
+ _test_cast(
+ np.arange(6.0, dtype=np.int32).reshape((1, 6)),
cast_dtype=tf.int64, use_mlir=use_mlir
+ )
#######################################################################
