def _tensor_field_by_type(tensor_val, builtin_type):
if builtin_type == types.bool:
return tensor_val.bools.values
elif types.is_int(builtin_type):
if (builtin_type == types.int64 or builtin_type == types.uint64):
return tensor_val.longInts.values
if builtin_type in (types.int8, types.uint8, types.uint32):
return tensor_val.bytes.values
return tensor_val.ints.values
elif types.is_float(builtin_type):
if (builtin_type == types.fp64):
return tensor_val.doubles.values
elif (builtin_type == types.fp32):
return tensor_val.floats.values
elif (builtin_type == types.fp16):
return tensor_val.bytes.values
else:
raise TypeError(
"Unsupported float dtype for MIL proto serialization: {}".
format(builtin_to_string(builtin_type)))
elif builtin_type == types.str:
return tensor_val.strings.values
else:
raise NotImplementedError("Unimplemented tensor type for: " +
str(builtin_type))
def _adjust_main_inputs(func):
first_op = func.operations[0] if len(func.operations) > 0 else None
for input_name, input_var in func.inputs.items():
if (types.is_tensor(input_var.sym_type) or types.is_scalar(input_var.sym_type)) \
and input_var.dtype != types.fp32 \
and input_var.dtype != types.int32:
input_dtype_str = types.builtin_to_string(input_var.dtype)
if types.is_int(input_var.dtype):
# Replace non-int32 input type with int32.
logging.warning("Input" + input_var.name + " is of dtype " + input_dtype_str +\
". Only integer variables of bit width 32 are supported by the CoreML runtime. " +\
"This input will be assigned a dtype of int32. " +\
"No cast will be inserted; the previous dtype will be replaced.")
_adjust_var_dtype_helper(input_var, types.int32)
elif input_var.dtype == types.fp64:
# Replace float64 input type with fp32.
logging.warning("Input '" + input_var.name + "' is of dtype fp64. 64 bit float inputs are " +\
"not supported by ML program models. This input will be assigned a dtype " +\
"of fp32. No cast will be inserted; the previous dtype will be replaced.")
_adjust_var_dtype_helper(input_var, types.fp32)
elif input_var.dtype == types.fp16 \
and func.opset_version >= target.iOS16:
pass # do nothing, since fp16 is a valid input type for CoreML
else:
# This is some other dtype. Change the type to fp32 and add a cast.
# This is only a limitation of main--other functions do not represent CoreML model inputs
# and do not have the same limitation on input types.
supported_dtypes = "{int32, fp32, fp64}" if func.opset_version < target.iOS16 else \
"{int32, fp16, fp32, fp64}"
msg = "\nInput '{}' is of dtype {}. The " +\
"CoreML runtime does not support inputs with this dtype " +\
"(supported dtypes are: {}). This input will be assigned a dtype of " +\
"fp32. A cast will be inserted at the beginning of the program to " +\
"convert the input to the originally defined dtype.\n"
if input_var.dtype == types.fp16:
msg += "fp16 dtype input is supported if the function.opset_version is chosen to be at least " \
"iOS16/macOS13.\n"
logging.warning(
msg.format(input_var.name, input_dtype_str,
supported_dtypes))
casted_input_var = mb.cast(x=input_var,
dtype=input_dtype_str,
before_op=first_op)
func.replace_uses_of_var_after_op(
anchor_op=casted_input_var.op,
old_var=input_var,
new_var=casted_input_var)
_adjust_var_dtype_helper(input_var, types.fp32)
def _adjust_main_inputs(func):
first_op = func.operations[0] if len(func.operations) > 0 else None
for input_name, input_var in func.inputs.items():
if (_types.is_tensor(input_var.sym_type) or _types.is_scalar(input_var.sym_type)) \
and input_var.dtype != _types.fp32 \
and input_var.dtype != _types.int32:
input_dtype_str = _types.builtin_to_string(input_var.dtype)
if _types.is_int(input_var.dtype):
# Replace non-int32 input type with int32.
_warnings.warn("Input" + input_var.name + " is of dType " + input_dtype_str +\
". Only integer variables of bit width 32 are supported by the CoreML runtime. " +\
"This input will be assigned a dType of int32. " +\
"No cast will be inserted; the previous dtype will be replaced.")
_adjust_var_dtype_helper(input_var, _types.int32)
elif input_var.dtype == _types.fp64:
# Replace float64 input type with fp32.
_warnings.warn("Input" + input_var.name + " is of dtype fp64. 64 bit float inputs are " +\
"not supported by ML program models. This input will be assigned a dType " +\
"of fp32. No cast will be inserted; the previous dtype will be replaced.")
_adjust_var_dtype_helper(input_var, _types.fp32)
else:
# This is some other dType. Change the type to fp32 and add a cast.
# This is only a limitation of main--other functions do not represent CoreML model inputs
# and do not have the same limitation on input types.
_warnings.warn("Input" + input_var.name + " is of dType " + input_dtype_str + ". The " +\
"CoreML runtime does not support inputs with this dType (only fp32 and " +\
"int32 inputs are supported). This input will be assigned a dType of " +\
"fp32. A cast will be inserted at the beginning of the program to " +\
"convert the input to the originally defined dType.")
with func:
casted_input_var = _mb.cast(x=input_var,
dtype=input_dtype_str,
before_op=first_op)
func.replace_uses_of_var_after_op(
anchor_op=casted_input_var.op,
old_var=input_var,
new_var=casted_input_var)
_adjust_var_dtype_helper(input_var, _types.fp32)
def _adjust_var(var):
"""
Changes the dtype of the provided variable according
to the rules outlined in the top level pass comment
(see adjust_io_to_supported_types).
"""
if (types.is_tensor(var.sym_type) or types.is_scalar(var.sym_type)) \
and var.dtype not in __RUNTIME_SUPPORTED_TYPES:
dtype_str = types.builtin_to_string(var.dtype)
if types.is_int(var.dtype):
# Replace non-int32 input type with int32.
logging.warning("Input '" + var.name + "' is of dtype " + dtype_str +\
". Only integer variables of bit width 32 are supported by the CoreML runtime. " +\
"This input will be assigned a dtype of int32. " +\
"No cast will be inserted; the previous dtype will be replaced.")
_adjust_var_dtype_helper(var, types.int32)
else:
# This is some other unsupported dtype. Change the input type to fp32.
logging.warning("Var " + var.name + " is of dtype " + dtype_str + ". The CoreML runtime " +\
"does not support this dtype (only fp16, fp32, bool, and int32 are supported). " +\
"This input will be assigned a dtype of fp32. No cast will be inserted; " +\
"the previous dtype will be replaced.")
_adjust_var_dtype_helper(var, types.fp32)