[API compatibility] add dtype conversion method

python/paddle/base/dygraph/math_op_patch.py

@@ -65,6 +65,36 @@
 _already_patch_eager_tensor = False
 
 
+_supported_dtype_conversions = {
+ # float
+ 'float16': 'float16',
+ 'half': 'float16',
+ 'bfloat16': 'bfloat16',
+ 'float32': 'float32',
+ 'float': 'float32',
+ 'float64': 'float64',
+ 'double': 'float64',
+ # int
+ 'int8': 'int8',
+ 'char': 'int8',
+ # We handle uint8 conversion separately
+ # 'uint8': 'uint8',
+ # 'byte': 'uint8',
+ 'int16': 'int16',
+ 'short': 'int16',
+ 'int32': 'int32',
+ 'int': 'int32',
+ 'int64': 'int64',
+ 'long': 'int64',
+ # other
+ 'bool': 'bool',
+ 'complex64': 'complex64',
+ 'complex128': 'complex128',
+ 'cfloat': 'complex64',
+ 'cdouble': 'complex128',
+}
+
+
 def monkey_patch_math_tensor():
  """
  Similar to monkey_patch_variable.
@@ -104,6 +134,44 @@ def astype(self: Tensor, dtype: DTypeLike) -> Tensor:
 
  return _C_ops.cast(self, dtype)
 
+ def byte(self: Tensor) -> Tensor:
+ # since paddle don't support float to uint8, so we need to convert it to int8 first
+ if self.is_floating_point():
+ tensor = astype(self, 'int8')
+ return astype(tensor, 'uint8')
+ elif self.is_complex():
+ real = astype(self.real(), 'int8')
+ return astype(real, 'uint8')
+ else:
+ return astype(self, 'uint8')
+
+ def _create_dtype_conversion_methods():
+ """
+ Batch create all data type conversion methods
+ """
+ methods = []
+
+ for method_name, target_dtype in _supported_dtype_conversions.items():
+
+ def make_conversion_method(dtype):
+ def conversion_method(self: Tensor) -> Tensor:
+ return astype(self, dtype)
+
+ return conversion_method
+
+ method_impl = make_conversion_method(target_dtype)
+ method_impl.__name__ = method_name
+ method_impl.__doc__ = f"""
+ Cast a Tensor to {target_dtype} data type if it differs from the current dtype;
+ otherwise, return the original Tensor.
+ Returns:
+ Tensor: a new Tensor with {target_dtype} dtype
+ """
+
+ methods.append((method_name, method_impl))
+
+ return methods
+
  def _scalar_elementwise_op_(
  var: Tensor, scale: float, bias: float
  ) -> Tensor:
@@ -225,6 +293,8 @@ def _mT_(var: Tensor) -> Tensor:
  ('__len__', _len_),
  ('__index__', _index_),
  ('astype', astype),
+ ('byte', byte),
+ ('uint8', byte),
  ('dim', dim),
  ('ndimension', ndimension),
  ('ndim', _ndim),
@@ -235,6 +305,9 @@ def _mT_(var: Tensor) -> Tensor:
  ('__array_ufunc__', None),
  ]
 
+ dtype_conversion_methods = _create_dtype_conversion_methods()
+ eager_methods.extend(dtype_conversion_methods)
+
  eager_cpp_level_patch = [
  "__add__",
  "__radd__",

python/paddle/pir/math_op_patch.py

@@ -37,6 +37,35 @@
  DataType.INT64,
 ]
 
+_supported_dtype_conversions = {
+ # float
+ 'float16': 'float16',
+ 'half': 'float16',
+ 'bfloat16': 'bfloat16',
+ 'float32': 'float32',
+ 'float': 'float32',
+ 'float64': 'float64',
+ 'double': 'float64',
+ # int
+ 'int8': 'int8',
+ 'char': 'int8',
+ # We handle uint8 conversion separately
+ # 'uint8': 'uint8',
+ # 'byte': 'uint8',
+ 'int16': 'int16',
+ 'short': 'int16',
+ 'int32': 'int32',
+ 'int': 'int32',
+ 'int64': 'int64',
+ 'long': 'int64',
+ # other
+ 'bool': 'bool',
+ 'complex64': 'complex64',
+ 'complex128': 'complex128',
+ 'cfloat': 'complex64',
+ 'cdouble': 'complex128',
+}
+
 SUPPORT_PROMOTION_OPS = [
  "__add__",
  "__radd__",
@@ -370,6 +399,41 @@ def astype(self, dtype):
 
  return _C_ops.cast(self, dtype)
 
+ def byte(self):
+ # since paddle don't support float to uint8, so we need to convert it to int8 first
+ if self.is_floating_point():
+ tensor = astype(self, 'int8')
+ return astype(tensor, 'uint8')
+ elif self.is_complex():
+ real = astype(self.real(), 'int8')
+ return astype(real, 'uint8')
+ else:
+ return astype(self, 'uint8')
+
+ def _create_dtype_conversion_methods():
+ """
+ Batch create all data type conversion methods
+ """
+ methods = []
+ for method_name, target_dtype in _supported_dtype_conversions.items():
+
+ def make_conversion_method(dtype):
+ def conversion_method(self):
+ return astype(self, dtype)
+
+ return conversion_method
+
+ method_impl = make_conversion_method(target_dtype)
+ method_impl.__name__ = method_name
+ method_impl.__doc__ = f"""
+ Cast a Value to {target_dtype} data type if it differs from the current dtype;
+ otherwise, return the original Value.
+ Returns:
+ Value: a new Value with {target_dtype} dtype
+ """
+ methods.append((method_name, method_impl))
+ return methods
+
  def _scalar_add_(var, value):
  return paddle.scale(var, 1.0, value)
 
@@ -1109,6 +1173,8 @@ def register_hook(self, hook):
  ('ndimension', ndimension),
  ('ndim', _ndim),
  ('astype', astype),
+ ('byte', byte),
+ ('uint8', byte),
  ('size', _size_),
  ('T', _T_),
  ('mT', _mT_),
@@ -1253,6 +1319,8 @@ def register_hook(self, hook):
  ('__bool__', _bool_),
  ('__complex__', _complex_),
  ]
+ dtype_conversion_methods = _create_dtype_conversion_methods()
+ value_methods.extend(dtype_conversion_methods)
 
  global _already_patch_value
  if not _already_patch_value: