siju-samuel commented on a change in pull request #4978: [TFLITE]Activation
functions support
URL: https://github.com/apache/incubator-tvm/pull/4978#discussion_r386862168
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File path: python/tvm/relay/frontend/tflite.py
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@@ -454,6 +456,45 @@ def convert_l2_normalization(self, op):
return out
+ def convert_lrn(self, op):
+ """Convert TFLite LOCAL_RESPONSE_NORMALIZATION """
+ try:
+ from tflite.Operator import Operator
+ from tflite.BuiltinOptions import BuiltinOptions
+ from tflite.LocalResponseNormalizationOptions import
LocalResponseNormalizationOptions
+ except ImportError:
+ raise ImportError("The tflite package must be installed")
+
+ assert isinstance(op, Operator)
+ if self.is_quantized(op):
+ raise tvm.error.OpNotImplemented(
+ 'TFlite quantized LRN operator is not supported yet.')
+
+ 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"
+
+ assert op.BuiltinOptionsType() ==
BuiltinOptions.LocalResponseNormalizationOptions
+ op_options = op.BuiltinOptions()
+ lrn_options = LocalResponseNormalizationOptions()
+ lrn_options.Init(op_options.Bytes, op_options.Pos)
+ radius = lrn_options.Radius()
+ bias = lrn_options.Bias()
+ alpha = lrn_options.Alpha()
+ beta = lrn_options.Beta()
+ size = (radius * 2) + 1
+ alpha = alpha * size
+
+ # TFLite supports lrn only over the last dim
+ input_tensor_rank = len(input_tensor.tensor.ShapeAsNumpy())
+ axis = input_tensor_rank - 1
Review comment:
Yes, same, nhwc format. axis=3
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