diff options
Diffstat (limited to 'ethosu/vela/tensor.py')
| -rw-r--r-- | ethosu/vela/tensor.py | 35 |
1 files changed, 14 insertions, 21 deletions
diff --git a/ethosu/vela/tensor.py b/ethosu/vela/tensor.py index 7dbdcddf..677757ca 100644 --- a/ethosu/vela/tensor.py +++ b/ethosu/vela/tensor.py @@ -254,20 +254,8 @@ class QuantizationParameters: res.quant_max = self.quant_max return res - def dequantize(self, values): - if self.zero_point.size == 1 and self.scale_f32.size == 1: - # same scale is used for all values - res = (values.astype(np.float64) - self.zero_point) * self.scale_f32 - else: - # a different scale is used for different sets of values - values_as_float = values.astype(np.float64) - - # this is not compatible with the format of depthwise weights, - # where input is at index 3 (Output, Kh, Kw, Input) - # return the quantized values - return np.ndarray((values_as_float.shape)) - - return res + def dequantize(self, values) -> np.ndarray: + return np.subtract(values, self.zero_point) * self.scale_f32 def is_scaling_equal(self, other: Optional["QuantizationParameters"]) -> bool: # quantisation parameter scaling is not equal if 'other' is None because @@ -300,16 +288,12 @@ def create_const_tensor( value_dtype: np.dtype = None, purpose: TensorPurpose = TensorPurpose.Unknown, quantization: QuantizationParameters = None, - quant_value_dtype: np.dtype = None, ): # Tensor const_tensor = Tensor(shape, dtype, name + "_0") const_tensor.purpose = purpose const_tensor.quantization = quantization const_tensor.values = np.array(values, dtype=value_dtype) - const_tensor.quant_values = np.frombuffer( - const_tensor.values.tobytes(), dtype=np.uint8 if not quant_value_dtype else quant_value_dtype - ) # Operator const_op = Operation(Op.Const, name) const_op.set_output_tensor(const_tensor) @@ -349,7 +333,6 @@ class Tensor: "ops", "consumer_list", "values", - "quant_values", "compressed_values", "compressed_values_substream_offsets", "mem_area", @@ -391,8 +374,7 @@ class Tensor: self.ops: List[Operation] = [] self.consumer_list: List[Operation] = [] - self.values: Optional[np.ndarray] = None - self.quant_values: Optional[np.ndarray] = None + self.values: Optional[np.ndarray] = None # elements are of type self.dtype self.compressed_values: Optional[np.ndarray] = None self.compressed_values_substream_offsets: Optional[List] = None self.mem_area: MemArea = MemArea.Unknown @@ -816,6 +798,17 @@ class Tensor: return (self.dtype.type & BaseType.Int) != 0 and self.quantization.is_valid() + def get_scalar(self): + """ + return: Unquantized or dequantized scalar value + rtype: self.dtype (if unquantized) or float (if dequantized) + """ + assert self.values.size == 1, "get_scalar called on non-scalar tensor" + if self.is_quantized(): + return self.quantization.dequantize(self.values).item(0) + else: + return self.values.item(0) + def __lt__(self, other: "Tensor") -> bool: return self.equivalence_id < other.equivalence_id |