wyc-ruiker commented on a change in pull request #4971: [TFLITE]FLOOR_MOD &
FLOOR_DIV support
URL: https://github.com/apache/incubator-tvm/pull/4971#discussion_r386006490
##########
File path: python/tvm/relay/frontend/tflite.py
##########
@@ -1532,6 +1534,58 @@ def convert_pad(self, op):
out = _op.nn.pad(in_expr, pad_width=paddings, pad_value=pad_value)
return out
+ def convert_floor_div(self, op):
+ """Convert TFLite FLOOR_DIV"""
+ if self.is_quantized(op):
+ raise tvm.error.OpNotImplemented(
+ 'TFlite quantized FLOOR DIV operator is not supported yet.')
+
+ input_tensors = self.get_input_tensors(op)
+ assert len(input_tensors) == 2, "input tensors length should be 2"
+
+ lhs_tensor = input_tensors[0]
+ if self.has_expr(lhs_tensor.tensor_idx):
+ lhs_expr = self.get_expr(lhs_tensor.tensor_idx)
+ else:
+ lhs_type_str = self.get_tensor_type_str(lhs_tensor.tensor.Type())
+ lhs_expr =
self.exp_tab.new_const(self.get_tensor_value(lhs_tensor),
+ dtype=lhs_type_str)
+ rhs_tensor = input_tensors[1]
+ if self.has_expr(rhs_tensor.tensor_idx):
+ rhs_expr = self.get_expr(rhs_tensor.tensor_idx)
+ else:
+ rhs_type_str = self.get_tensor_type_str(rhs_tensor.tensor.Type())
+ rhs_expr =
self.exp_tab.new_const(self.get_tensor_value(rhs_tensor),
+ dtype=rhs_type_str)
+ out = _op.floor_divide(lhs_expr, rhs_expr)
+ return out
+
+ def convert_floor_mod(self, op):
+ """Convert TFLite FLOOR_MOD"""
+ if self.is_quantized(op):
+ raise tvm.error.OpNotImplemented(
+ 'TFlite quantized FLOOR MOD operator is not supported yet.')
+
+ input_tensors = self.get_input_tensors(op)
+ assert len(input_tensors) == 2, "input tensors length should be 2"
+
+ lhs_tensor = input_tensors[0]
+ if self.has_expr(lhs_tensor.tensor_idx):
+ lhs_expr = self.get_expr(lhs_tensor.tensor_idx)
+ else:
+ lhs_type_str = self.get_tensor_type_str(lhs_tensor.tensor.Type())
+ lhs_expr =
self.exp_tab.new_const(self.get_tensor_value(lhs_tensor),
+ dtype=lhs_type_str)
+ rhs_tensor = input_tensors[1]
+ if self.has_expr(rhs_tensor.tensor_idx):
+ rhs_expr = self.get_expr(rhs_tensor.tensor_idx)
+ else:
+ rhs_type_str = self.get_tensor_type_str(rhs_tensor.tensor.Type())
+ rhs_expr =
self.exp_tab.new_const(self.get_tensor_value(rhs_tensor),
+ dtype=rhs_type_str)
Review comment:
Same as above.
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