def __init__(self,
node_name,
cname,
pool_params,
act_params,
gen_ctrl=None,
at_ver=3,
force_relu=True):
if gen_ctrl is None:
self.gen_ctrl = GenCtrl(None, cname=cname)
else:
gen_ctrl.cname = cname
self.gen_ctrl = gen_ctrl
if act_params is not None:
self.at_act_params = gen_active_at_params(act_params,
force_relu=force_relu)
else:
self.at_act_params = NO_ACTIVATION
pad_compatibilities = []
self.at_pool_params = gen_pool_at_params(pool_params,
pad_compatibilities)
self.in_dim = pool_params.in_dims[0]
self.out_dim = pool_params.out_dims[0]
self.cname = cname
self.node_name = node_name
self.at_ver = at_ver
def __init__(self,
node_name,
cname,
pool_params,
act_params,
qrec,
act_q=None,
gen_ctrl=None,
at_ver=3,
force_relu=True):
if gen_ctrl is None:
self.gen_ctrl = GenCtrl(None, cname=cname)
else:
gen_ctrl.cname = cname
self.gen_ctrl = gen_ctrl
if pool_params.ker_in_order and pool_params.ker_in_order[0] == [
"h", "w", "c"
]:
self.gen_ctrl.hwc = 1
if not qrec.out_qs[0].signed:
self.gen_ctrl.output_datasize = -qrec.out_qs[0].dtype_bits // 8
if not qrec.in_qs[0].signed:
self.gen_ctrl.input_datasize = -qrec.in_qs[0].dtype_bits // 8
if act_params is not None:
self.at_act_params = gen_active_at_params(
act_params,
force_relu=force_relu,
asymmetric=act_q.in_qs[0].zero_point != 0)
else:
self.at_act_params = NO_ACTIVATION
pad_compatibilities = []
self.at_pool_params = gen_pool_at_params(pool_params,
pad_compatibilities)
self.in_dim = pool_params.in_dims[0]
self.out_dim = pool_params.out_dims[0]
self.cname = cname
self.node_name = node_name
self.at_ver = at_ver
def __init__(self,
node_name,
cname,
conv_params,
conv_q,
pool_params,
pool_q,
act_params,
act_q,
at_ver=3,
gen_ctrl=None):
self.ne16 = False
if gen_ctrl is None:
self.gen_ctrl = gen_ctrl = GenCtrl(None, cname=cname)
else:
gen_ctrl.cname = cname
self.gen_ctrl = gen_ctrl
in_q = filter_q = out_q = bias_q = mul_biases_q = None
in_dim = out_dim = None
pad_compatibilities = []
if conv_params is not None:
if conv_params.ker_in_order and conv_params.ker_in_order[0] == [
"h", "w", "c"
]:
self.hwc = True
self.gen_ctrl.hwc = 1
at_conv_params = gen_conv_at_params(conv_params,
pad_compatibilities)
in_dim = conv_params.in_dims[0]
out_dim = conv_params.out_dims[0]
# Set ENABLEIM2COL on 1x1 filters by default
if conv_params.filter.h == 1 and conv_params.filter.w == 1 and gen_ctrl.enableim2col is None:
gen_ctrl.enableim2col = 1
filter_q = conv_q.in_qs[1]
in_q = conv_q.in_qs[0]
out_q = conv_q.out_qs[0]
bias_q = conv_q.in_qs[2]
if conv_params.has_mul_bias:
mul_biases_q = conv_q.mul_biases_q
self.ne16 = conv_q.cache.get('ne16')
else:
at_conv_params = NO_CONV
if pool_params is not None:
if pool_params.ker_in_order and pool_params.ker_in_order[0] == [
"h", "w", "c"
]:
self.hwc = True
self.gen_ctrl.hwc = 1
at_pool_params = gen_pool_at_params(pool_params,
pad_compatibilities)
if in_dim is None:
in_dim = pool_params.in_dims[0]
out_dim = pool_params.out_dims[0]
if in_q is None:
in_q = pool_q.in_qs[0]
out_q = pool_q.out_qs[0]
else:
at_pool_params = NO_POOL
if act_params is not None:
if act_params.ker_in_order and act_params.ker_in_order[0] == [
"h", "w", "c"
]:
self.hwc = True
self.gen_ctrl.hwc = 1
if in_q is None:
in_q = act_q.in_qs[0]
at_act_params = gen_active_at_params(
act_params,
force_relu=False,
asymmetric=act_q.in_qs[0].zero_point != 0)
if isinstance(act_params,
ReluActivationParameters) and act_params.upper_bound:
self.gen_ctrl.relun = act_params.upper_bound
if in_dim is None:
in_dim = act_params.in_dims[0].expand_to_chw()
if out_dim is None:
out_dim = act_params.out_dims[0].expand_to_chw()
out_q = act_q.out_qs[0]
else:
at_act_params = NO_ACTIVATION
if pad_compatibilities:
reduction = PadDim.pad_compatibility_reduce(
*pad_compatibilities,
"convolution padding is not compatible with pool padding")
if not reduction[2]: # default is balanced pad left
at_pad_ctrl = next(i for i, v in enumerate(reduction) if v)
LOG.debug("%s: generating pad control block", node_name)
self.gen_ctrl.PadType = at_pad_ctrl
self.in_dim = in_dim
self.out_dim = out_dim
self.in_q = in_q
self.bias_q = bias_q
self.out_q = out_q
self.filter_q = filter_q
self.mul_biases_q = mul_biases_q
self.at_act_params = at_act_params
self.at_pool_params = at_pool_params
self.at_conv_params = at_conv_params
self.cname = cname
self.node_name = node_name
self.at_ver = at_ver
def __init__(self,
node_name,
cname,
conv_params,
conv_q,
pool_params,
pool_q,
act_params,
act_q,
at_ver=3,
gen_ctrl=None,
force_relu=True):
if gen_ctrl is None:
self.gen_ctrl = gen_ctrl = GenCtrl(None, cname=cname)
else:
gen_ctrl.cname = cname
self.gen_ctrl = gen_ctrl
in_q = filter_q = out_q = bias_q = mul_biases_q = None
in_dim = out_dim = None
pad_compatibilities = []
if conv_params is not None:
at_conv_params = gen_conv_at_params(conv_params,
pad_compatibilities)
in_dim = conv_params.in_dims[0]
out_dim = conv_params.out_dims[0]
# Set ENABLEIM2COL on 1x1 filters by default
if conv_params.filter.h == 1 and conv_params.filter.w == 1 and gen_ctrl.enableim2col is None:
gen_ctrl.enableim2col = 1
filter_q = conv_q.in_qs[1]
in_q = conv_q.in_qs[0]
out_q = conv_q.out_qs[0]
bias_q = conv_q.in_qs[2]
if conv_params.has_mul_bias:
mul_biases_q = conv_q.mul_biases_q
else:
at_conv_params = NO_CONV
if pool_params is not None:
at_pool_params = gen_pool_at_params(pool_params,
pad_compatibilities)
if in_dim is None:
in_dim = pool_params.in_dims[0]
out_dim = pool_params.out_dims[0]
if in_q is None:
in_q = pool_q.in_qs[0]
out_q = pool_q.out_qs[0]
else:
at_pool_params = NO_POOL
if act_params is not None:
at_act_params = gen_active_at_params(act_params,
force_relu=force_relu)
if in_dim is None:
in_dim = act_params.in_dims[0].expand_to_chw()
if out_dim is None:
out_dim = act_params.out_dims[0].expand_to_chw()
if in_q is None:
in_q = act_q.in_qs[0]
out_q = act_q.out_qs[0]
else:
at_act_params = NO_ACTIVATION
if pad_compatibilities:
reduction = PadDim.pad_compatibility_reduce(
*pad_compatibilities,
"convolution padding is not compatible with pool padding")
if not reduction[2]: # default is balanced pad left
at_pad_ctrl = next(i for i, v in enumerate(reduction) if v)
LOG.debug("%s: generating pad control block", node_name)
self.gen_ctrl.PadType = at_pad_ctrl
self.in_dim = in_dim
self.out_dim = out_dim
self.in_q = in_q
self.bias_q = bias_q
self.out_q = out_q
self.filter_q = filter_q
self.mul_biases_q = mul_biases_q
self.at_act_params = at_act_params
self.at_pool_params = at_pool_params
self.at_conv_params = at_conv_params
self.cname = cname
self.node_name = node_name
self.at_ver = at_ver
def __init__(self,
node_name,
cname,
pool_params,
pool_q,
act_params,
act_q,
force_relu,
gen_ctrl=None):
if gen_ctrl is None:
self.gen_ctrl = gen_ctrl = GenCtrl(None, cname=cname)
else:
gen_ctrl.cname = cname
self.gen_ctrl = gen_ctrl
if pool_params.ker_in_order and pool_params.ker_in_order[0] == [
"h", "w", "c"
]:
hwc = True
gen_ctrl.hwc = 1
pad_compatibilities = []
at_pool_params = gen_pool_at_params(pool_params, pad_compatibilities)
in_dim = pool_params.in_dims[0]
out_dim = pool_params.out_dims[0]
in_q = pool_q.in_qs[0]
out_q = pool_q.out_qs[0]
if act_params is not None:
act_op = gen_activation_op(
act_params.activation,
force_relu=force_relu,
asymmetric=act_q.in_qs[0].zero_point != 0)
if out_dim is None:
out_dim = act_params.out_dims[0].expand_to_chw()
out_q = act_q.out_qs[0]
else:
act_op = "KOP_NONE"
if pad_compatibilities:
reduction = PadDim.pad_compatibility_reduce(
*pad_compatibilities,
"convolution padding is not compatible with pool padding")
if not reduction[2]: # default is balanced pad left
at_pad_ctrl = next(i for i, v in enumerate(reduction) if v)
LOG.debug("%s: generating pad control block", node_name)
self.gen_ctrl.PadType = at_pad_ctrl
attrs = {
'in_size':
in_q.dtype_bits // 8 if in_q.signed else -in_q.dtype_bits // 8,
'out_size':
out_q.dtype_bits // 8 if out_q.signed else -out_q.dtype_bits // 8,
'feat':
in_dim.c,
'width':
in_dim.w,
'height':
in_dim.h,
'kop_pool':
at_pool_params.PoolOper,
'fpx':
at_pool_params.Fpx,
'fpy':
at_pool_params.Fpy,
'dpx':
at_pool_params.Dpx,
'dpy':
at_pool_params.Dpy,
'spx':
at_pool_params.Spx,
'spy':
at_pool_params.Spy,
'pool_pad':
at_pool_params.PoolPad,
'kop_act':
act_op
}
extra_attrs = {'cname': cname, 'node_name': node_name}
super().__init__(attrs, extra_attrs, gen_ctrl=gen_ctrl)
def __init__(self, node_name, cname, conv_params, conv_q, pool_params, pool_q, act_params, act_q, force_relu, gen_ctrl=None):
if gen_ctrl is None:
self.gen_ctrl = gen_ctrl = GenCtrl(None, cname=cname)
else:
gen_ctrl.cname = cname
self.gen_ctrl = gen_ctrl
is_ne16 = conv_q.cache.get('ne16')
hwc = False
if not is_ne16 and conv_params.ker_in_order and conv_params.ker_in_order[0] == ["h", "w", "c"]:
hwc = True
gen_ctrl.hwc = 1
if not is_ne16 and not hwc and conv_params.filter.h == 1 and conv_params.filter.w == 1 and gen_ctrl.enableim2col is None:
gen_ctrl.enableim2col = 1
in_q = filter_q = out_q = bias_q = None
in_dim = out_dim = None
pad_compatibilities = []
at_conv_params = gen_conv_at_params(
conv_params, pad_compatibilities)
in_dim = conv_params.in_dims[0]
out_dim = conv_params.out_dims[0]
filter_q = conv_q.in_qs[1]
in_q = conv_q.in_qs[0]
out_q = conv_q.out_qs[0]
bias_q = conv_q.in_qs[2]
pad_val = in_q.zero_point[0]
if pool_params is not None:
at_pool_params = gen_pool_at_params(
pool_params, pad_compatibilities)
out_dim = pool_params.out_dims[0]
out_q = pool_q.out_qs[0]
else:
at_pool_params = NO_POOL
if act_params is not None:
act_op = gen_activation_op(
act_params.activation, force_relu=force_relu, asymmetric=act_q.in_qs[0].zero_point != 0)
if out_dim is None:
out_dim = act_params.out_dims[0].expand_to_chw()
out_q = act_q.out_qs[0]
else:
act_op = "KOP_NONE"
if pad_compatibilities:
reduction = PadDim.pad_compatibility_reduce(*pad_compatibilities,
"convolution padding is not compatible with pool padding")
if not reduction[2]: # default is balanced pad left
at_pad_ctrl = next(i for i, v in enumerate(reduction) if v)
LOG.debug("%s: generating pad control block", node_name)
self.gen_ctrl.PadType = at_pad_ctrl
attrs = {
'in_size': in_q.dtype_bits//8 if in_q.signed else -in_q.dtype_bits//8,
'out_size': out_q.dtype_bits//8 if out_q.signed else -out_q.dtype_bits//8,
'bias_size': bias_q.dtype_bits//8,
'filter_bits': filter_q.bits,
'in_feat': in_dim.c,
'out_feat': out_dim.c,
'in_width': in_dim.w,
'in_height': in_dim.h,
'kop_conv': at_conv_params.ConvOper,
'fcx': at_conv_params.Fcx,
'fcy': at_conv_params.Fcy,
'dcx': at_conv_params.Dcx,
'dcy': at_conv_params.Dcy,
'scx': at_conv_params.Scx,
'scy': at_conv_params.Scy,
'conv_pad': at_conv_params.ConvPad,
'pad_value': pad_val,
'kop_pool': at_pool_params.PoolOper,
'fpx': at_pool_params.Fpx,
'fpy': at_pool_params.Fpy,
'dpx': at_pool_params.Dpx,
'dpy': at_pool_params.Dpy,
'spx': at_pool_params.Spx,
'spy': at_pool_params.Spy,
'pool_pad': at_pool_params.PoolPad,
'kop_act': act_op
}
extra_attrs = {
'cname': cname,
'node_name': node_name
}
super().__init__(attrs, extra_attrs, gen_ctrl=gen_ctrl)
