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new 2355caa [Frontend][TFLite] Add parser support for l2_normalization
(#4966)
2355caa is described below
commit 2355caa8afdc8e6a3638c9514f57686737cbd724
Author: Ina Dobreva <[email protected]>
AuthorDate: Sat Feb 29 23:30:16 2020 +0200
[Frontend][TFLite] Add parser support for l2_normalization (#4966)
* [Frontend][TFLite] Add parser support for l2_normalization
* TF doesn't provide uint8 support
* TFL does the normalization only if it's over the last axis
* TFL uses only the default value for expilon
* Change error message
---
python/tvm/relay/frontend/tflite.py | 47 ++++++++++++++++++++++++++++
tests/python/frontend/tflite/test_forward.py | 20 ++++++++++++
2 files changed, 67 insertions(+)
diff --git a/python/tvm/relay/frontend/tflite.py
b/python/tvm/relay/frontend/tflite.py
index 3a17083..5d26d98 100644
--- a/python/tvm/relay/frontend/tflite.py
+++ b/python/tvm/relay/frontend/tflite.py
@@ -122,6 +122,7 @@ class OperatorConverter(object):
'LOGICAL_OR': self.convert_logical_or,
'DETECTION_POSTPROCESS': self.convert_detection_postprocess,
'SQUARE': self.convert_square,
+ 'L2_NORMALIZATION': self.convert_l2_normalization,
}
def check_unsupported_ops(self):
@@ -405,6 +406,52 @@ class OperatorConverter(object):
"""Convert TFLite RESIZE_NEAREST_NEIGHBOR"""
return self._convert_resize("nearest_neighbor", op)
+ def convert_l2_normalization(self, op):
+ """Convert TFLite L2_NORMALIZATION """
+ try:
+ from tflite.Operator import Operator
+ from tflite.BuiltinOptions import BuiltinOptions
+ from tflite.L2NormOptions import L2NormOptions
+ from tflite.ActivationFunctionType import ActivationFunctionType
+ except ImportError:
+ raise ImportError("The tflite package must be installed")
+
+ assert isinstance(op, Operator)
+ input_tensors = self.get_input_tensors(op)
+ assert len(input_tensors) == 1, "input tensors length should be 1"
+ input_tensor = input_tensors[0]
+ in_expr = self.get_expr(input_tensor.tensor_idx)
+
+ output_tensors = self.get_output_tensors(op)
+ assert len(output_tensors) == 1, "output tensors length should be 1"
+ output_tensor = output_tensors[0]
+
+ assert op.BuiltinOptionsType() == BuiltinOptions.L2NormOptions
+ op_options = op.BuiltinOptions()
+ l2_norm_options = L2NormOptions()
+ l2_norm_options.Init(op_options.Bytes, op_options.Pos)
+ fused_activation_fn = l2_norm_options.FusedActivationFunction()
+
+ # TFLite supports normalization only over the last dim
+ input_tensor_rank = len(input_tensor.tensor.ShapeAsNumpy())
+
+ if self.is_quantized(op):
+ raise tvm.error.OpNotImplemented(
+ 'TFLite quantized L2_NORMALIZATION operator is not supported
yet.')
+ # TFL uses only the default epsilon value
+ out = _op.nn.l2_normalize(in_expr, eps=1e-12, axis=[input_tensor_rank
- 1])
+
+ # if we have fused activation fn
+ if fused_activation_fn != ActivationFunctionType.NONE:
+ if not output_tensor.qnn_params:
+ out = self.convert_fused_activation_function(out,
fused_activation_fn)
+ else:
+ raise tvm.error.OpNotImplemented(
+ 'TFLite quantized L2_NORMALIZATION operator\
+ with fused activation function is not supported yet.')
+
+ return out
+
def convert_logistic(self, op):
"""Convert TFLite LOGISTIC"""
try:
diff --git a/tests/python/frontend/tflite/test_forward.py
b/tests/python/frontend/tflite/test_forward.py
index 4a16325..ced2425 100644
--- a/tests/python/frontend/tflite/test_forward.py
+++ b/tests/python/frontend/tflite/test_forward.py
@@ -33,6 +33,7 @@ from tensorflow.python.ops import math_ops
from tensorflow.python.ops import nn_ops
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gen_array_ops
+from tensorflow.python.ops import nn_impl
from tensorflow.python.ops import variables
try:
from tensorflow import lite as interpreter_wrapper
@@ -1264,6 +1265,24 @@ def test_forward_unpack():
_test_unpack(np.array(np.random.uniform(0, 5, (2, 3, 4)),
dtype=np.int32), axis=-3, num_unpacks=2)
#######################################################################
+# L2 normalization
+# ----------------
+
+def _test_l2_normalization(data, axis, fused_activation_function=None):
+ """ One iteration of L2_NORMALIZATION """
+ with tf.Graph().as_default():
+ in_data = array_ops.placeholder(shape=data.shape, dtype=data.dtype)
+ out = nn_impl.l2_normalize(in_data, axis)
+ out = with_fused_activation_function(out, fused_activation_function)
+ compare_tflite_with_tvm(data, 'Placeholder:0', [in_data], [out])
+
+def test_forward_l2_normalization():
+ """ L2_NORMALIZATION """
+ data = np.random.uniform(size=(3, 6, 4)).astype('float32')
+ _test_l2_normalization(data, axis=2)
+ _test_l2_normalization(data, axis=2, fused_activation_function="RELU")
+
+#######################################################################
# Logistic
# --------
@@ -1649,6 +1668,7 @@ if __name__ == '__main__':
test_forward_relu()
test_forward_prelu()
test_forward_fully_connected()
+ test_forward_l2_normalization()
# Elemwise
test_all_elemwise()
