from akida.core import (Layer, LayerParams, LayerType)
[docs]
class Dense2D(Layer):
"""Dense layer capable of working on 2D inputs.
The 2D Dense operation is simply the repetition of a 1D
FullyConnected/Dense operation over each input row.
Inputs shape mush be in the form (1, X, Y). Being the result of a quantized
operation, it is possible to apply some shifts to adjust the inputs/outputs
scales to the equivalent operation performed on floats, while maintaining
a limited usage of bits and performing the operations on integer values.
The 2D Dense operation can be described as follows:
>>> inputs = inputs << input_shift
>>> prod = matmul(inputs, weights)
>>> output = prod + (bias << bias_shift)
>>> output = output * output_scale >> output_shift
Inputs shape must be (1, X, Y). Note that output values will be saturated
on the range that can be represented with output_bits.
Args:
units (int): Positive integer, dimensionality of the output space.
output_bits (int, optional): output bitwidth. Defaults to 8.
buffer_bits (int, optional): buffer bitwidth. Defaults to 32.
post_op_buffer_bits (int, optional): internal bitwidth for post operations.
Defaults to 32.
activation (bool, optional): apply a ReLU activation. Defaults to False.
name (str, optional): name of the layer. Defaults to empty string.
"""
def __init__(self,
units,
output_bits=8,
buffer_bits=32,
post_op_buffer_bits=32,
activation=False,
name=""):
try:
params = LayerParams(
LayerType.Dense2D, {
"units": units,
"output_bits": output_bits,
"buffer_bits": buffer_bits,
"post_op_buffer_bits": post_op_buffer_bits,
"activation": activation,
})
# Call parent constructor to initialize C++ bindings
# Note that we invoke directly __init__ instead of using super, as
# specified in pybind documentation
Layer.__init__(self, params, name)
except BaseException:
self = None
raise