Perform hybrid quantized convolution of float Tensor lhs
and quantized Tensor rhs
.
tf.raw_ops.UniformQuantizedConvolutionHybrid(
lhs,
rhs,
rhs_scales,
rhs_zero_points,
Tout,
padding,
rhs_quantization_min_val,
rhs_quantization_max_val,
window_strides=[],
explicit_padding=[],
lhs_dilation=[],
rhs_dilation=[],
batch_group_count=1,
feature_group_count=1,
dimension_numbers='',
rhs_quantization_axis=-1,
name=None
)
Given float lhs
and quantized rhs
, internally performs quantization on lhs
,
and then performs quantized convolution on quantized lhs
and rhs
.
The internal quantization on lhs
is a quantization to Trhs
, dynamic range,
per-batch (per-axis along axis dimension_numbers.input_batch_dimension
), asymmetric,
and not narrow range (the range is [Trhs_MIN, Trhs_MAX]).
lhs
and rhs
must be Tensors of same rank, and meet following shape conditions.
- lhs_feature % feature_group_count == 0
- lhs_feature % rhs_input_feature == 0
- lhs_feature / feature_group_count == rhs_input_feature
- rhs_output_feature % feature_group_count == 0
- lhs_batch % batch_group_count == 0
- rhs_output_feature % batch_group_count == 0
rhs
must be quantized Tensor, where its data value is quantized using the formula:
quantized_data = clip(original_data / scale + zero_point, quantization_min_val, quantization_max_val).
Args | |
---|---|
lhs
|
A Tensor . Must be one of the following types: float32 .
Must be a non-quantized Tensor of Tlhs , rank >= 3.
|
rhs
|
A Tensor . Must be one of the following types: qint8 .
Must be a quantized Tensor of Trhs , same rank as lhs .
|
rhs_scales
|
A Tensor of type float32 .
The float value(s) used as scale factors when quantizing the original data that rhs represents.
Must be a scalar Tensor for per-tensor quantization,
or 1D Tensor of size rhs.dim_size(kernel_output_feature_dimension) , for per-channel quantization.
|
rhs_zero_points
|
A Tensor of type int32 .
The int32 value(s) used as zero_point when quantizing original data that rhs represents.
Same shape condition as rhs_scales .
|
Tout
|
A tf.DType from: tf.float32 . The type of output Tensor.
|
padding
|
A string .
string from: "SAME" , "VALID" , or "EXPLICIT" , indicating the type of padding algorithm to use.
|
rhs_quantization_min_val
|
An int .
The min value of the quantized data stored in rhs .
For example, if Trhs is qint8, this must be set to -127 if narrow range quantized or -128 if not.
|
rhs_quantization_max_val
|
An int .
The max value of the quantized data stored in rhs .
For example, if Trhs is qint8, this must be set to 127.
|
window_strides
|
An optional list of ints . Defaults to [] .
The stride of the sliding window for each spatial dimension of lhs .
Must be an empty list (default) or a list of size (number of spatial dimensions).
If an empty list is provided, the stride for each spatial dimension is set to 1.
|
explicit_padding
|
An optional list of ints . Defaults to [] .
If padding Attr is "EXPLICIT" , must be set as a list indicating
the explicit paddings at the start and end of each lhs spatial dimension.
Otherwise, this Attr is must be empty.
(If used,) Must be a list of size 2 * (number of lhs spatial dimensions), where (explicit_padding[2 * i], explicit_padding[2 * i + 1]) indicates spatial_dimensionsi. |
lhs_dilation
|
An optional list of ints . Defaults to [] .
The dilation factor to apply in each spatial dimension of lhs .
Must be an empty list (default) or a list of size (number of lhs spatial dimensions).
If empty list, the dilation for each lhs spatial dimension is set to 1.
|
rhs_dilation
|
An optional list of ints . Defaults to [] .
The dilation factor to apply in each spatial dimension of rhs .
Must be an empty list (default) or a list of size (number of rhs spatial dimensions).
If empty list, the dilation for each rhs spatial dimension is set to 1.
|
batch_group_count
|
An optional int . Defaults to 1 .
The number of batch groups. Used for grouped filters.
Must be a divisor of output_feature.
|
feature_group_count
|
An optional int . Defaults to 1 .
The number of feature groups. Used for grouped convolutions.
Must be a divisor of both lhs_feature and output_feature.
|
dimension_numbers
|
An optional string . Defaults to "" .
Structure of dimension information for the convolution op.
Must be an empty string (default) or a serialized string of tensorflow.UniformQuantizedConvolutionDimensionNumbersAttr proto.
If empty string, the default is ("NCHW", "OIHW", "NCHW") (for a 2D convolution).
|
rhs_quantization_axis
|
An optional int . Defaults to -1 .
Indicates the dimension index of the tensor where per-axis quantization is applied for the slices along that dimension.
If set to -1 (default), this indicates per-tensor quantization.
For the rhs , only per-tensor quantization
or per-channel quantization along kernel_output_feature_dimension is supported.
Thus, this attribute must be set to -1 or dimension_numbers.kernel_output_feature_dimension .
Other values will raise error at OpKernel construction.
|
name
|
A name for the operation (optional). |
Returns | |
---|---|
A Tensor of type Tout .
|