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new 6ed3ab3e33 [TFLite] Support quantized EQUAL op in TFLite frontend
(#11520)
6ed3ab3e33 is described below
commit 6ed3ab3e33f8eafa4acaf53b7a671831de7587e9
Author: Dhruv Chauhan <[email protected]>
AuthorDate: Wed Jun 22 10:42:00 2022 +0100
[TFLite] Support quantized EQUAL op in TFLite frontend (#11520)
* [TFLite] Support quantized EQUAL op in TFLite frontend
Support EQUAL quantization operation conversion as part of issue #9187
* [TFLite] Support quantized EQUAL op in TFLite frontend
Update elementwise quantized test for EQUAL op
Change-Id: I3897d1ac07051ebfc10356ad45397117b592f878
---
python/tvm/relay/frontend/tflite.py | 6 +--
tests/python/frontend/tflite/test_forward.py | 81 +++++++++++++++++++---------
2 files changed, 57 insertions(+), 30 deletions(-)
diff --git a/python/tvm/relay/frontend/tflite.py
b/python/tvm/relay/frontend/tflite.py
index 981074b6ad..2a9d66acff 100644
--- a/python/tvm/relay/frontend/tflite.py
+++ b/python/tvm/relay/frontend/tflite.py
@@ -1448,11 +1448,7 @@ class OperatorConverter(object):
def convert_equal(self, op):
"""Convert TFLite EQUAL"""
- if self.is_quantized(op):
- raise tvm.error.OpNotImplemented(
- "TFlite quantized EQUAL operator is not supported yet."
- )
- return self._convert_elemwise(_op.equal, op)
+ return self._convert_elemwise(_op.equal, op, self.is_quantized(op))
def convert_not_equal(self, op):
"""Convert TFLite NOT_EQUAL"""
diff --git a/tests/python/frontend/tflite/test_forward.py
b/tests/python/frontend/tflite/test_forward.py
index 76b0766dae..23b5a03ffb 100644
--- a/tests/python/frontend/tflite/test_forward.py
+++ b/tests/python/frontend/tflite/test_forward.py
@@ -2214,22 +2214,33 @@ def _test_elemwise(
if None != x[0]
}
- out = math_op(inq_data[0], inq_data[1])
- out = with_fused_activation_function(out,
fused_activation_function)
- out = tf.quantization.fake_quant_with_min_max_args(
- out, min=out_min, max=out_max, name="out"
- )
+ if math_op is math_ops.equal:
+ out = math_op(inq_data[0], inq_data[1])
+ out = with_fused_activation_function(out,
fused_activation_function)
- # Note same_qnn_params uses experimental_new_converter as toco
failed
- compare_tflite_with_tvm(
- [x[1] for x in zip(in_data, data) if None != x[0]],
- [x + ":0" for x in input_range.keys()],
- [x[1] for x in zip(in_data, inq_data) if None != x[0]],
- [out],
- quantized=True,
- input_range=input_range,
- experimental_new_converter=same_qnn_params,
- )
+ compare_tflite_with_tvm(
+ [x[1] for x in zip(in_data, data) if None != x[0]],
+ [x + ":0" for x in input_range.keys()],
+ [x[1] for x in zip(in_data, inq_data) if None != x[0]],
+ [out],
+ )
+ else:
+ out = math_op(inq_data[0], inq_data[1])
+ out = with_fused_activation_function(out,
fused_activation_function)
+ out = tf.quantization.fake_quant_with_min_max_args(
+ out, min=out_min, max=out_max, name="out"
+ )
+
+ # Note same_qnn_params uses experimental_new_converter as toco
failed
+ compare_tflite_with_tvm(
+ [x[1] for x in zip(in_data, data) if None != x[0]],
+ [x + ":0" for x in input_range.keys()],
+ [x[1] for x in zip(in_data, inq_data) if None != x[0]],
+ [out],
+ quantized=True,
+ input_range=input_range,
+ experimental_new_converter=same_qnn_params,
+ )
else:
out = math_op(
in_data[0]
@@ -2386,9 +2397,16 @@ def _test_less_equal(data):
# -----
-def _test_equal(data):
+def _test_equal(data, fused_activation_function=None, quantized=False,
qnn_op=None):
"""One iteration of equal"""
- return _test_elemwise(math_ops.equal, data)
+ return _test_elemwise(
+ math_ops.equal,
+ data,
+ fused_activation_function,
+ quantized,
+ qnn_op,
+ same_qnn_params=True,
+ )
#######################################################################
@@ -2454,14 +2472,25 @@ def _test_forward_elemwise(testop):
def _test_forward_elemwise_quantized(testop):
- testop(
- [
- np.array(np.random.uniform(0, 255, (3, 6)), dtype=np.uint8),
- np.array(np.random.uniform(0, 255, (3, 6)), dtype=np.uint8),
- ],
- quantized=True,
- qnn_op=testop,
- )
+ if testop is not _test_equal:
+ testop(
+ [
+ np.array(np.random.uniform(0, 255, (3, 6)), dtype=np.uint8),
+ np.array(np.random.uniform(0, 255, (3, 6)), dtype=np.uint8),
+ ],
+ quantized=True,
+ qnn_op=testop,
+ )
+ else:
+ # no need for fake_quant to hold tensors in float32 until conversion
+ testop(
+ [
+ np.array(np.random.uniform(0, 255, (3, 6)), dtype=np.float32),
+ np.array(np.random.uniform(0, 255, (3, 6)), dtype=np.float32),
+ ],
+ quantized=True,
+ qnn_op=testop,
+ )
def _test_elemwise_qnn_out_range(qnn_op):
@@ -2472,6 +2501,7 @@ def _test_elemwise_qnn_out_range(qnn_op):
_test_mul: (-5e3, 5e3),
_test_maximum: (-112, 111),
_test_minimum: (-128, 127),
+ _test_equal: (-150, 150),
}
return qnn_out_range[qnn_op]
@@ -2506,6 +2536,7 @@ def test_all_elemwise():
_test_forward_elemwise(_test_less)
_test_forward_elemwise(_test_less_equal)
_test_forward_elemwise(_test_equal)
+ _test_forward_elemwise_quantized(_test_equal)
_test_forward_elemwise(_test_not_equal)
if package_version.parse(tf.VERSION) >= package_version.parse("1.14.0"):
_test_forward_elemwise(_test_floor_divide)
