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wuwei pushed a commit to branch main
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The following commit(s) were added to refs/heads/main by this push:
new a3991b32ca [Relay/Op] Use f-strings for string formatting, NFC (#14831)
a3991b32ca is described below
commit a3991b32caec1478ed66260b58f3c5e12cf037a3
Author: Krzysztof Parzyszek <[email protected]>
AuthorDate: Fri May 12 01:04:28 2023 -0500
[Relay/Op] Use f-strings for string formatting, NFC (#14831)
* [Relay/Op] Use f-strings for string formatting, NFC
Replace uses of % and .format() with f-strings.
* Reformat modified files
* No f-strings in hybrid script...
---
python/tvm/relay/op/annotation/annotation.py | 2 +-
python/tvm/relay/op/contrib/cutlass.py | 2 +-
python/tvm/relay/op/contrib/dnnl.py | 19 ++----
python/tvm/relay/op/nn/_nn.py | 15 ++---
python/tvm/relay/op/nn/utils.py | 6 +-
python/tvm/relay/op/op.py | 10 ++--
python/tvm/relay/op/strategy/adreno.py | 10 +---
python/tvm/relay/op/strategy/arm_cpu.py | 32 ++++------
python/tvm/relay/op/strategy/bifrost.py | 10 +---
python/tvm/relay/op/strategy/cuda.py | 37 +++++-------
python/tvm/relay/op/strategy/generic.py | 83 +++++++-------------------
python/tvm/relay/op/strategy/hexagon.py | 4 +-
python/tvm/relay/op/strategy/hls.py | 6 +-
python/tvm/relay/op/strategy/intel_graphics.py | 4 +-
python/tvm/relay/op/strategy/mali.py | 12 ++--
python/tvm/relay/op/strategy/x86.py | 28 ++++-----
python/tvm/relay/op/tensor.py | 2 +-
python/tvm/relay/op/transform.py | 4 +-
python/tvm/relay/op/vision/_rcnn.py | 4 +-
19 files changed, 102 insertions(+), 188 deletions(-)
diff --git a/python/tvm/relay/op/annotation/annotation.py
b/python/tvm/relay/op/annotation/annotation.py
index 685a8807f7..71a434917e 100644
--- a/python/tvm/relay/op/annotation/annotation.py
+++ b/python/tvm/relay/op/annotation/annotation.py
@@ -30,7 +30,7 @@ def _make_virtual_device(device):
return target.VirtualDevice(_nd.device(device))
if isinstance(device, target.VirtualDevice):
return device
- raise ValueError("expecting a Device or device name, but received a %s" %
(type(device)))
+ raise ValueError(f"expecting a Device or device name, but received a
{type(device)}")
def on_device(body, device, constrain_result=False, constrain_body=True):
diff --git a/python/tvm/relay/op/contrib/cutlass.py
b/python/tvm/relay/op/contrib/cutlass.py
index 6fce020a66..40fc22e9e8 100644
--- a/python/tvm/relay/op/contrib/cutlass.py
+++ b/python/tvm/relay/op/contrib/cutlass.py
@@ -88,7 +88,7 @@ def make_conv2d_pattern(with_bias=False, with_act=None):
)
return is_op("multiply")(conv2d_out, rhs)
- raise ValueError("Unknown activation %s." % with_act)
+ raise ValueError(f"Unknown activation {with_act}.")
return conv2d_out
diff --git a/python/tvm/relay/op/contrib/dnnl.py
b/python/tvm/relay/op/contrib/dnnl.py
index cc8848b236..71a126ae8f 100644
--- a/python/tvm/relay/op/contrib/dnnl.py
+++ b/python/tvm/relay/op/contrib/dnnl.py
@@ -45,14 +45,7 @@ from tvm.relay.expr import Call, GlobalVar, TupleGetItem,
const
from tvm.relay.expr_functor import ExprMutator, ExprVisitor
from ... import _ffi_api
-from ...dataflow_pattern import (
- DFPatternCallback,
- is_constant,
- is_expr,
- is_op,
- rewrite,
- wildcard,
-)
+from ...dataflow_pattern import DFPatternCallback, is_constant, is_expr,
is_op, rewrite, wildcard
from .register import register_pattern_table
logger = logging.getLogger("DNNL")
@@ -172,7 +165,7 @@ def make_conv_pattern(conv_name, with_bias=True,
with_eltwise=None):
Call node sequence.
"""
if with_eltwise not in supported_post_elts:
- raise ValueError("Unsupported eltwise post-op: %s" % with_eltwise)
+ raise ValueError(f"Unsupported eltwise post-op: {with_eltwise}")
data = wildcard()
weight = wildcard()
bias = wildcard()
@@ -335,7 +328,7 @@ def make_dense_pattern(with_bias=True, with_eltwise=None):
Call node sequence.
"""
if with_eltwise not in supported_post_elts:
- raise ValueError("Unsupported eltwise post-op: %s" % with_eltwise)
+ raise ValueError(f"Unsupported eltwise post-op: {with_eltwise}")
data = wildcard()
weight = wildcard()
bias = wildcard()
@@ -579,7 +572,7 @@ def get_shape(tensor):
if tensor.op.name == "multiply":
return tensor.type_args[0].shape
return tensor.checked_type.shape
- raise TypeError("Unsupport data type: %s" % type(tensor))
+ raise TypeError(f"Unsupport data type: {type(tensor)}")
def get_dtype(tensor):
@@ -596,7 +589,7 @@ def get_dtype(tensor):
if tensor.op.name == "multiply":
return tensor.type_args[0].dtype
return tensor.checked_type.dtype
- raise TypeError("Unsupport data type: %s" % type(tensor))
+ raise TypeError(f"Unsupport data type: {type(tensor)}")
def tag2layout(input_data, is_weight=False, conv_type="Conv1D"):
@@ -627,7 +620,7 @@ def tag2layout(input_data, is_weight=False,
conv_type="Conv1D"):
elif i.isdigit():
res += i
else:
- raise ValueError("Unsupport layout format: %s" % input_data)
+ raise ValueError(f"Unsupport layout format: {input_data}")
return res
diff --git a/python/tvm/relay/op/nn/_nn.py b/python/tvm/relay/op/nn/_nn.py
index b93285aed8..c68685f0ae 100644
--- a/python/tvm/relay/op/nn/_nn.py
+++ b/python/tvm/relay/op/nn/_nn.py
@@ -307,7 +307,7 @@ def convert_conv2d(attrs, inputs, tinfos, desired_layouts):
new_attrs["kernel_layout"] = desired_kernel_layout
return relay.nn.contrib_conv2d_nchwc(data, weight, **new_attrs)
- raise ValueError("Layout %s is not yet supported." % desired_data_layout)
+ raise ValueError(f"Layout {desired_data_layout} is not yet supported.")
# conv2d_transpose
@@ -375,7 +375,7 @@ def convert_conv2d_transpose(attrs, inputs, tinfos,
desired_layouts):
new_attrs["kernel_layout"] = "HWIO"
return relay.nn.conv2d_transpose(data, weight, **new_attrs)
- raise ValueError("Layout %s is not yet supported." % desired_data_layout)
+ raise ValueError(f"Layout {desired_data_layout} is not yet supported.")
# conv3d_transpose
@@ -424,7 +424,7 @@ def convert_conv3d_transpose(attrs, inputs, tinfos,
desired_layouts):
new_attrs["kernel_layout"] = "DHWOI"
return relay.nn.conv3d_transpose(data, weight, **new_attrs)
- raise ValueError("Layout %s is not yet supported" % desired_data_layout)
+ raise ValueError(f"Layout {desired_data_layout} is not yet supported")
@reg.register_legalize("nn.conv3d_transpose")
@@ -498,7 +498,7 @@ def convert_conv3d(attrs, inputs, tinfos, desired_layouts):
new_attrs["kernel_layout"] = "DHWIO"
return relay.nn.conv3d(data, weight, **new_attrs)
- raise ValueError("Layout %s is not yet supported" % desired_data_layout)
+ raise ValueError(f"Layout {desired_data_layout} is not yet supported")
# conv3d_winograd related operators
@@ -917,7 +917,7 @@ def convert_deformable_conv2d(attrs, inputs, tinfos,
desired_layouts):
elif desired_data_layout == "NHWC":
new_attrs["kernel_layout"] = "HWIO"
else:
- raise ValueError("Layout %s is not yet supported." %
desired_data_layout)
+ raise ValueError(f"Layout {desired_data_layout} is not yet supported.")
return relay.nn.deformable_conv2d(data, offset, weight, **new_attrs)
@@ -1457,10 +1457,7 @@ def dense_shape_func(attrs, inputs, _):
"""
ret = [
_matmul_shape_func(
- inputs[0],
- inputs[1],
- expr.IntImm("bool", False),
- expr.IntImm("bool", True),
+ inputs[0], inputs[1], expr.IntImm("bool", False),
expr.IntImm("bool", True)
)
]
return ret
diff --git a/python/tvm/relay/op/nn/utils.py b/python/tvm/relay/op/nn/utils.py
index fc687cfe07..0286f0a8f4 100644
--- a/python/tvm/relay/op/nn/utils.py
+++ b/python/tvm/relay/op/nn/utils.py
@@ -45,7 +45,7 @@ def get_pad_tuple1d(padding):
elif isinstance(padding, int):
pad_w = padding * 2
else:
- raise ValueError("Unknown padding option %s" % padding)
+ raise ValueError(f"Unknown padding option {padding}")
pad_left = (pad_w + 1) // 2
return pad_left, pad_w - pad_left
@@ -81,7 +81,7 @@ def get_pad_tuple2d(padding):
elif isinstance(padding, int):
pad_h = pad_w = padding * 2
else:
- raise ValueError("Unknown padding option %s" % padding)
+ raise ValueError(f"Unknown padding option {padding}")
pad_top = (pad_h + 1) // 2
pad_left = (pad_w + 1) // 2
return pad_top, pad_left, pad_h - pad_top, pad_w - pad_left
@@ -123,7 +123,7 @@ def get_pad_tuple3d(padding):
elif isinstance(padding, int):
pad_d = pad_h = pad_w = padding * 2
else:
- raise ValueError("Unknown padding option %s" % padding)
+ raise ValueError(f"Unknown padding option {padding}")
pad_front = (pad_d + 1) // 2
pad_top = (pad_h + 1) // 2
pad_left = (pad_w + 1) // 2
diff --git a/python/tvm/relay/op/op.py b/python/tvm/relay/op/op.py
index ec48ea175f..5f37845ceb 100644
--- a/python/tvm/relay/op/op.py
+++ b/python/tvm/relay/op/op.py
@@ -192,15 +192,15 @@ def _wrap_default_fstrategy(compute, schedule, name):
def _create_fstrategy_from_schedule(op_name, schedule):
assert hasattr(schedule, "dispatch_dict")
compute = get(op_name).get_attr("FTVMCompute")
- assert compute is not None, "FTVMCompute is not registered for op %s" %
op_name
- fstrategy = get_native_generic_func("{}_strategy".format(op_name))
+ assert compute is not None, f"FTVMCompute is not registered for op
{op_name}"
+ fstrategy = get_native_generic_func(f"{op_name}_strategy")
name_pfx = schedule.__name__
name_pfx = name_pfx[name_pfx.index("_") + 1 :]
fstrategy.set_default(
- _wrap_default_fstrategy(compute, schedule.fdefault, "%s.generic" %
name_pfx)
+ _wrap_default_fstrategy(compute, schedule.fdefault,
f"{name_pfx}.generic")
)
for key, sch in schedule.dispatch_dict.items():
- fstrategy.register(_wrap_default_fstrategy(compute, sch, "%s.%s" %
(name_pfx, key)), [key])
+ fstrategy.register(_wrap_default_fstrategy(compute, sch,
f"{name_pfx}.{key}"), [key])
return fstrategy
@@ -522,7 +522,7 @@ def debug(expr, debug_func=None):
global __DEBUG_COUNTER__
if debug_func:
- name = "debugger_func{}".format(__DEBUG_COUNTER__)
+ name = f"debugger_func{__DEBUG_COUNTER__}"
tvm._ffi.register_func(name, debug_func)
__DEBUG_COUNTER__ += 1
else:
diff --git a/python/tvm/relay/op/strategy/adreno.py
b/python/tvm/relay/op/strategy/adreno.py
index b606ab05d7..712b66e246 100644
--- a/python/tvm/relay/op/strategy/adreno.py
+++ b/python/tvm/relay/op/strategy/adreno.py
@@ -109,7 +109,7 @@ def conv2d_strategy_adreno(attrs, inputs, out_type, target):
elif data_layout == "NHWC4c":
ic = data.shape[3] * data.shape[4]
else:
- raise RuntimeError("Unsupported depthwise_conv2d data layout
{}".format(data_layout))
+ raise RuntimeError(f"Unsupported depthwise_conv2d data layout
{data_layout}")
if kernel_layout == "OIHW":
oc = kernel.shape[0]
elif kernel_layout == "OIHW4o":
@@ -119,9 +119,7 @@ def conv2d_strategy_adreno(attrs, inputs, out_type, target):
elif kernel_layout == "HWOI4o":
oc = kernel.shape[2] * kernel.shape[4]
else:
- raise RuntimeError(
- "Unsupported depthwise_conv2d kernel layout
{}".format(kernel_layout)
- )
+ raise RuntimeError(f"Unsupported depthwise_conv2d kernel layout
{kernel_layout}")
if ic == oc == groups:
if (data_layout == "NCHW" and kernel_layout == "OIHW") or (
@@ -186,9 +184,7 @@ def
conv2d_winograd_without_weight_transform_strategy_adreno(attrs, inputs, out_
plevel=5,
)
else:
- raise RuntimeError(
- "Unsupported conv2d_winograd_without_weight_transform layout
{}".format(layout)
- )
+ raise RuntimeError(f"Unsupported
conv2d_winograd_without_weight_transform layout {layout}")
return strategy
diff --git a/python/tvm/relay/op/strategy/arm_cpu.py
b/python/tvm/relay/op/strategy/arm_cpu.py
index 6e6c1bf03b..dc3b16aa82 100644
--- a/python/tvm/relay/op/strategy/arm_cpu.py
+++ b/python/tvm/relay/op/strategy/arm_cpu.py
@@ -180,9 +180,7 @@ def conv2d_strategy_arm_cpu(attrs, inputs, out_type,
target):
name="conv2d_nchw_spatial_pack.arm_cpu",
)
else:
- raise RuntimeError(
- "Unsupported weight layout {} for conv2d
NCHW".format(kernel_layout)
- )
+ raise RuntimeError(f"Unsupported weight layout {kernel_layout}
for conv2d NCHW")
elif layout == "HWCN":
assert kernel_layout == "HWIO"
logger.warning("conv2d_hwcn is not optimized for arm cpu.")
@@ -237,12 +235,10 @@ def conv2d_strategy_arm_cpu(attrs, inputs, out_type,
target):
name="conv2d_nhwc_spatial_pack.arm_cpu",
)
else:
- raise RuntimeError(
- "Unsupported kernel layout {} for conv2d
NHWC".format(kernel_layout)
- )
+ raise RuntimeError(f"Unsupported kernel layout {kernel_layout}
for conv2d NHWC")
else:
- raise RuntimeError("Unsupported conv2d layout {} for arm
cpu".format(layout))
+ raise RuntimeError(f"Unsupported conv2d layout {layout} for arm
cpu")
elif is_depthwise_conv2d(data.shape, layout, kernel.shape, kernel_layout,
groups):
if layout == "NCHW":
assert kernel_layout == "OIHW" or re.match(r"OIHW\d*o",
kernel_layout)
@@ -329,7 +325,7 @@ def conv2d_strategy_arm_cpu(attrs, inputs, out_type,
target):
name="depthwise_conv2d_nhwc.generic",
)
else:
- raise RuntimeError("Unsupported depthwise_conv2d layout {} for arm
cpu".format(layout))
+ raise RuntimeError(f"Unsupported depthwise_conv2d layout {layout}
for arm cpu")
else: # group_conv2d
if layout == "NCHW":
assert kernel_layout == "OIHW"
@@ -347,7 +343,7 @@ def conv2d_strategy_arm_cpu(attrs, inputs, out_type,
target):
name="group_conv2d_nhwc.generic",
)
else:
- raise RuntimeError("Unsupported group_conv2d layout {} for arm
cpu".format(layout))
+ raise RuntimeError(f"Unsupported group_conv2d layout {layout} for
arm cpu")
return strategy
@@ -439,11 +435,9 @@ def
conv2d_winograd_without_weight_transform_strategy_arm_cpu(attrs, inputs, out
plevel=15,
)
else:
- raise RuntimeError("Unsupported kernel shape:
{}".format(kernel.shape))
+ raise RuntimeError(f"Unsupported kernel shape: {kernel.shape}")
else:
- raise RuntimeError(
- "Unsupported conv2d_winograd_without_weight_transform layout
{}".format(layout)
- )
+ raise RuntimeError(f"Unsupported
conv2d_winograd_without_weight_transform layout {layout}")
return strategy
@@ -493,8 +487,8 @@ def
conv2d_gemm_without_weight_transform_strategy_arm_cpu(attrs, inputs, out_typ
)
else:
raise RuntimeError(
- "Unsupported conv2d_NHWC_quantized_without_transform layout {0}"
- "with datatype {1}".format(layout, data.dtype)
+ f"Unsupported conv2d_NHWC_quantized_without_transform layout
{layout}"
+ f"with datatype {data.dtype}"
)
return strategy
@@ -535,7 +529,7 @@ def bitserial_conv2d_strategy_arm_cpu(attrs, inputs,
out_type, target):
name="bitserial_conv2d_nhwc.arm_cpu",
)
else:
- raise ValueError("Data layout {} not supported.".format(layout))
+ raise ValueError(f"Data layout {layout} not supported.")
return strategy
@@ -612,9 +606,7 @@ def conv1d_strategy_arm_cpu(attrs, inputs, out_type,
target):
)
else:
raise RuntimeError(
- "Unsupported kernel layout {} for conv1d {} for arm
cpu.".format(
- kernel_layout, layout
- )
+ f"Unsupported kernel layout {kernel_layout} for conv1d
{layout} for arm cpu."
)
elif layout == "NCW":
logger.warning("conv1d with layout %s is not optimized for arm cpu.",
layout)
@@ -632,6 +624,6 @@ def conv1d_strategy_arm_cpu(attrs, inputs, out_type,
target):
)
else:
raise RuntimeError(
- "Unsupported kernel layout {} for conv1d {} for arm
cpu.".format(kernel_layout, layout)
+ f"Unsupported kernel layout {kernel_layout} for conv1d {layout}
for arm cpu."
)
return strategy
diff --git a/python/tvm/relay/op/strategy/bifrost.py
b/python/tvm/relay/op/strategy/bifrost.py
index 46ebb6048c..f437aa15f6 100644
--- a/python/tvm/relay/op/strategy/bifrost.py
+++ b/python/tvm/relay/op/strategy/bifrost.py
@@ -74,7 +74,7 @@ def conv2d_strategy_bifrost(attrs, inputs, out_type, target):
name="conv2d_nhwc_spatial_pack.bifrost",
)
else:
- raise RuntimeError("Unsupported conv2d layout {} for
Mali(Bifrost)".format(layout))
+ raise RuntimeError(f"Unsupported conv2d layout {layout} for
Mali(Bifrost)")
elif is_depthwise_conv2d(data.shape, layout, kernel.shape, kernel_layout,
groups):
if layout == "NCHW":
assert kernel_layout == "OIHW"
@@ -92,9 +92,7 @@ def conv2d_strategy_bifrost(attrs, inputs, out_type, target):
name="depthwise_conv2d_nchw.bifrost",
)
else:
- raise RuntimeError(
- "Unsupported depthwise_conv2d layout {} for
Mali(Bifrost)".format(layout)
- )
+ raise RuntimeError(f"Unsupported depthwise_conv2d layout {layout}
for Mali(Bifrost)")
else: # group_conv2d
raise RuntimeError("group_conv2d is not supported for Mali(Bifrost)")
return strategy
@@ -118,9 +116,7 @@ def
conv2d_winograd_without_weight_transform_strategy_bifrost(attrs, inputs, out
name="conv2d_nchw_winograd.bifrost",
)
else:
- raise RuntimeError(
- "Unsupported conv2d_winograd_without_weight_transform layout
{}".format(layout)
- )
+ raise RuntimeError(f"Unsupported
conv2d_winograd_without_weight_transform layout {layout}")
return strategy
diff --git a/python/tvm/relay/op/strategy/cuda.py
b/python/tvm/relay/op/strategy/cuda.py
index 65573321f7..1fd806b7cf 100644
--- a/python/tvm/relay/op/strategy/cuda.py
+++ b/python/tvm/relay/op/strategy/cuda.py
@@ -357,7 +357,7 @@ def conv2d_strategy_cuda(attrs, inputs, out_type, target):
)
elif target.kind.name == "cuda" and "cudnn" not in target.libs:
# No TVM native kernel applicable
- raise RuntimeError("Unsupported conv2d layout {} for
CUDA".format(layout))
+ raise RuntimeError(f"Unsupported conv2d layout {layout} for CUDA")
if (
target.kind.name == "cuda"
@@ -395,7 +395,7 @@ def conv2d_strategy_cuda(attrs, inputs, out_type, target):
name="depthwise_conv2d_nhwc.cuda",
)
else:
- raise RuntimeError("Unsupported depthwise_conv2d layout
{}".format(layout))
+ raise RuntimeError(f"Unsupported depthwise_conv2d layout {layout}")
else: # group_conv2d
# add cudnn implementation, if any
cudnn_impl = False
@@ -453,7 +453,7 @@ def conv2d_strategy_cuda(attrs, inputs, out_type, target):
name="group_conv2d_NCHWc_int8.cuda",
)
elif not cudnn_impl:
- raise RuntimeError("Unsupported group_conv2d layout
{}".format(layout))
+ raise RuntimeError(f"Unsupported group_conv2d layout {layout}")
return strategy
@@ -603,9 +603,7 @@ def
conv2d_winograd_without_weight_transform_strategy_cuda(attrs, inputs, out_ty
plevel=15,
)
else:
- raise RuntimeError(
- "Unsupported conv2d_winograd_without_weight_transform layout
{}".format(layout)
- )
+ raise RuntimeError(f"Unsupported
conv2d_winograd_without_weight_transform layout {layout}")
return strategy
@@ -629,7 +627,7 @@ def deformable_conv2d_strategy_cuda(attrs, inputs,
out_type, target):
name="deformable_conv2d_nhwc.cuda",
)
else:
- raise RuntimeError("Layout %s is not supported in deformable conv2d on
CUDA" % layout)
+ raise RuntimeError(f"Layout {layout} is not supported in deformable
conv2d on CUDA")
return strategy
@@ -689,10 +687,9 @@ def conv2d_transpose_strategy_cuda(attrs, inputs,
out_type, target):
num_strategies += 1
# TODO(masahi): Support conv2d_transpose NHWC for non-cudnn path.
- assert num_strategies > 0, "Unsupported conv2d_transpose workload, layout
= %s, groups = %d" % (
- layout,
- groups,
- )
+ assert (
+ num_strategies > 0
+ ), f"Unsupported conv2d_transpose workload, layout = {layout}, groups =
{groups}"
return strategy
@@ -722,7 +719,7 @@ def conv3d_strategy_cuda(attrs, inputs, out_type, target):
layout = attrs.data_layout
_, stride_h, stride_w = attrs.get_int_tuple("strides")
_, dilation_h, dilation_w = attrs.get_int_tuple("dilation")
- assert layout in ["NCDHW", "NDHWC"], "Not support this layout {}
yet".format(layout)
+ assert layout in ["NCDHW", "NDHWC"], f"Not support this layout {layout}
yet"
if layout == "NCDHW":
strategy.add_implementation(
wrap_compute_conv3d(topi.cuda.conv3d_ncdhw),
@@ -796,9 +793,7 @@ def
conv3d_winograd_without_weight_transform_strategy_cuda(attrs, inputs, out_ty
name="conv3d_ncdhw_winograd_without_weight_transform.cuda",
)
else:
- raise RuntimeError(
- "Unsupported conv3d_winograd_without_weight_transform layout
{}".format(layout)
- )
+ raise RuntimeError(f"Unsupported
conv3d_winograd_without_weight_transform layout {layout}")
return strategy
@@ -824,7 +819,7 @@ def conv1d_strategy_cuda(attrs, inputs, out_type, target):
name="conv1d_nwc.cuda",
)
else:
- raise ValueError("Unsupported conv1d layout {}".format(layout))
+ raise ValueError(f"Unsupported conv1d layout {layout}")
else:
if layout == "NCW":
strategy.add_implementation(
@@ -839,7 +834,7 @@ def conv1d_strategy_cuda(attrs, inputs, out_type, target):
name="group_conv1d_nwc.cuda",
)
else:
- raise ValueError("Unsupported conv1d layout {}".format(layout))
+ raise ValueError(f"Unsupported conv1d layout {layout}")
return strategy
@@ -868,15 +863,11 @@ def matmul_strategy_cuda(attrs, inputs, out_type, target):
if is_auto_scheduler_enabled():
strategy.add_implementation(
- wrap_compute_matmul(topi.nn.matmul),
- naive_schedule,
- name="matmul.cuda",
+ wrap_compute_matmul(topi.nn.matmul), naive_schedule,
name="matmul.cuda"
)
elif is_meta_schedule_enabled():
strategy.add_implementation(
- wrap_compute_matmul(topi.nn.matmul),
- naive_schedule,
- name="matmul.cuda",
+ wrap_compute_matmul(topi.nn.matmul), naive_schedule,
name="matmul.cuda"
)
else:
logger.warning(
diff --git a/python/tvm/relay/op/strategy/generic.py
b/python/tvm/relay/op/strategy/generic.py
index 2883e5e1fb..533d65ead7 100644
--- a/python/tvm/relay/op/strategy/generic.py
+++ b/python/tvm/relay/op/strategy/generic.py
@@ -67,12 +67,12 @@ def get_conv2d_in_channels(data_shape, data_layout):
data_shape = get_const_tuple(data_shape)
if len(data_shape) == 4:
idx = data_layout.find("C")
- assert idx >= 0, "Invalid conv2d data layout {}".format(data_layout)
+ assert idx >= 0, f"Invalid conv2d data layout {data_layout}"
return data_shape[idx]
if re.match(r"NCHW\d*c", data_layout):
# NCHW[8]c
return data_shape[1] * data_shape[4]
- raise ValueError("Unknown conv2d data layout {}".format(data_layout))
+ raise ValueError(f"Unknown conv2d data layout {data_layout}")
def get_conv2d_out_channels(kernel_shape, kernel_layout):
@@ -80,13 +80,13 @@ def get_conv2d_out_channels(kernel_shape, kernel_layout):
kernel_shape = get_const_tuple(kernel_shape)
if len(kernel_shape) == 4:
idx = kernel_layout.find("O")
- assert idx >= 0, "Invalid conv2d kernel layout
{}".format(kernel_layout)
+ assert idx >= 0, f"Invalid conv2d kernel layout {kernel_layout}"
return kernel_shape[idx]
if re.match(r"OIHW\d*i\d*o", kernel_layout):
return kernel_shape[0] * kernel_shape[5]
if re.match(r"OIHW\d*o", kernel_layout):
return kernel_shape[0] * kernel_shape[4]
- raise ValueError("Unknown conv2d kernel layout {}".format(kernel_layout))
+ raise ValueError(f"Unknown conv2d kernel layout {kernel_layout}")
def is_depthwise_conv2d(data_shape, data_layout, kernel_shape, kernel_layout,
groups):
@@ -302,7 +302,7 @@ def conv2d_strategy(attrs, inputs, out_type, target):
name="conv2d_hwcn.generic",
)
else:
- raise RuntimeError("Unsupported conv2d layout {}".format(layout))
+ raise RuntimeError(f"Unsupported conv2d layout {layout}")
elif is_depthwise_conv2d(data.shape, layout, kernel.shape, kernel_layout,
groups):
if layout == "NCHW":
assert kernel_layout == "OIHW"
@@ -319,7 +319,7 @@ def conv2d_strategy(attrs, inputs, out_type, target):
name="depthwise_conv2d_nhwc.generic",
)
else:
- raise RuntimeError("Unsupported depthwise_conv2d layout
{}".format(layout))
+ raise RuntimeError(f"Unsupported depthwise_conv2d layout {layout}")
else: # group_conv2d
if layout == "NCHW":
assert kernel_layout == "OIHW"
@@ -336,7 +336,7 @@ def conv2d_strategy(attrs, inputs, out_type, target):
name="group_conv2d_nhwc.generic",
)
else:
- raise RuntimeError("Unsupported group_conv2d layout
{}".format(layout))
+ raise RuntimeError(f"Unsupported group_conv2d layout {layout}")
return strategy
@@ -465,7 +465,7 @@ def deformable_conv2d_strategy(attrs, inputs, out_type,
target):
name="deformable_conv2d_nhwc.generic",
)
else:
- raise RuntimeError("Layout %s is not supported in deformable conv2d" %
layout)
+ raise RuntimeError(f"Layout {layout} is not supported in deformable
conv2d")
return strategy
@@ -608,7 +608,7 @@ def conv3d_strategy(attrs, inputs, out_type, target):
name="conv3d_ndhwc.generic",
)
else:
- raise ValueError("Not support this layout {} yet".format(layout))
+ raise ValueError(f"Not support this layout {layout} yet")
return strategy
@@ -665,7 +665,7 @@ def conv1d_strategy(attrs, inputs, out_type, target):
name="conv1d_nwc.generic",
)
else:
- raise ValueError("Unsupported conv1d layout {}".format(layout))
+ raise ValueError(f"Unsupported conv1d layout {layout}")
return strategy
@@ -708,7 +708,7 @@ def group_conv1d_strategy(attrs, inputs, out_type, target):
name="group_conv1d_nwc.generic",
)
else:
- raise ValueError("Unsupported conv1d layout {}".format(layout))
+ raise ValueError(f"Unsupported conv1d layout {layout}")
return strategy
@@ -796,7 +796,7 @@ def dilation2d_strategy(attrs, inputs, out_type, target):
name="dilation2d_nhwc.generic",
)
else:
- raise RuntimeError("Unsupported dilation2d layout {}".format(layout))
+ raise RuntimeError(f"Unsupported dilation2d layout {layout}")
return strategy
@@ -815,9 +815,7 @@ def copy_if_identical(tensor_a, tensor_b):
# matmul
def wrap_compute_matmul(
- topi_compute,
- need_auto_scheduler_layout=False,
- need_meta_schedule_layout=False,
+ topi_compute, need_auto_scheduler_layout=False,
need_meta_schedule_layout=False
):
"""wrap matmul topi compute"""
@@ -825,14 +823,7 @@ def wrap_compute_matmul(
"""Compute definition of matmul"""
out_dtype = attrs.out_dtype
out_dtype = inputs[0].dtype if out_dtype == "" else out_dtype
- args = [
- inputs[0],
- inputs[1],
- None,
- out_dtype,
- attrs.transpose_a,
- attrs.transpose_b,
- ]
+ args = [inputs[0], inputs[1], None, out_dtype, attrs.transpose_a,
attrs.transpose_b]
if need_auto_scheduler_layout:
args.append(get_auto_scheduler_rewritten_layout(attrs))
elif need_meta_schedule_layout:
@@ -859,9 +850,7 @@ def matmul_strategy(attrs, inputs, out_type, target):
# dense
def wrap_compute_dense(
- topi_compute,
- need_auto_scheduler_layout=False,
- need_meta_schedule_layout=False,
+ topi_compute, need_auto_scheduler_layout=False,
need_meta_schedule_layout=False
):
"""wrap dense topi compute"""
@@ -1309,12 +1298,7 @@ def wrap_compute_all_class_nms(topi_compute):
score_threshold = inputs[4]
output_format = attrs.output_format
return topi_compute(
- inputs[0],
- inputs[1],
- max_output_size,
- iou_threshold,
- score_threshold,
- output_format,
+ inputs[0], inputs[1], max_output_size, iou_threshold,
score_threshold, output_format
)
return _compute_nms
@@ -1480,11 +1464,7 @@ def wrap_compute_dft(topi_compute):
"""Wrap DFT compute"""
def _compute_dft(attrs, inputs, _):
- return topi_compute(
- inputs[0],
- inputs[1],
- attrs.inverse,
- )
+ return topi_compute(inputs[0], inputs[1], attrs.inverse)
return _compute_dft
@@ -1506,13 +1486,7 @@ def wrap_compute_trilu(topi_compute):
"""Wrap trilu compute"""
def _compute_trilu(attrs, inputs, output_type):
- return [
- topi_compute(
- inputs[0],
- inputs[1],
- attrs.upper,
- )
- ]
+ return [topi_compute(inputs[0], inputs[1], attrs.upper)]
return _compute_trilu
@@ -1663,7 +1637,7 @@ def bitserial_conv2d_strategy(attrs, inputs, out_type,
target):
name="bitserial_conv2d_nhwc.generic",
)
else:
- raise ValueError("Data layout {} not supported.".format(layout))
+ raise ValueError(f"Data layout {layout} not supported.")
return strategy
@@ -2033,15 +2007,7 @@ def wrap_compute_conv2d_backward_weight(topi_compute):
layout = attrs.data_layout
out_dtype = inputs[0].dtype if out_dtype in ("same", "") else out_dtype
out = topi_compute(
- inputs[0],
- inputs[1],
- kernel_size,
- padding,
- strides,
- dilation,
- groups,
- layout,
- out_dtype,
+ inputs[0], inputs[1], kernel_size, padding, strides, dilation,
groups, layout, out_dtype
)
return [out]
@@ -2074,13 +2040,6 @@ def wrap_compute_layout_transform(topi_compute,
schedule_rule="None"):
"""Wrap layout transform compute"""
def _compute_layout_transform(attrs, inputs, output_type):
- return [
- topi_compute(
- inputs[0],
- attrs.src_layout,
- attrs.dst_layout,
- schedule_rule,
- )
- ]
+ return [topi_compute(inputs[0], attrs.src_layout, attrs.dst_layout,
schedule_rule)]
return _compute_layout_transform
diff --git a/python/tvm/relay/op/strategy/hexagon.py
b/python/tvm/relay/op/strategy/hexagon.py
index f42503a147..2db3b2c886 100644
--- a/python/tvm/relay/op/strategy/hexagon.py
+++ b/python/tvm/relay/op/strategy/hexagon.py
@@ -92,7 +92,7 @@ def conv2d_strategy_hexagon(attrs, inputs, out_type, target):
name="depthwise_conv2d_nhwc.hexagon",
)
else:
- raise RuntimeError("Unsupported depthwise_conv2d layout
{}".format(layout))
+ raise RuntimeError(f"Unsupported depthwise_conv2d layout {layout}")
else: # group_conv2d
raise RuntimeError(f"Unsupported group_conv2d layout {layout}")
@@ -139,7 +139,7 @@ def conv2d_transpose_strategy_hexagon(attrs, inputs,
out_type, target):
name="conv2d_transpose_nchw.generic",
)
else:
- raise RuntimeError("Unsupported conv2d_transpose layout
{}".format(layout))
+ raise RuntimeError(f"Unsupported conv2d_transpose layout {layout}")
return strategy
diff --git a/python/tvm/relay/op/strategy/hls.py
b/python/tvm/relay/op/strategy/hls.py
index 4a682066ca..61f5a18e9c 100644
--- a/python/tvm/relay/op/strategy/hls.py
+++ b/python/tvm/relay/op/strategy/hls.py
@@ -109,7 +109,7 @@ def conv2d_strategy_hls(attrs, inputs, out_type, target):
name="conv2d_nhwc.hls",
)
else:
- raise RuntimeError("Unsupported conv2d layout {}".format(layout))
+ raise RuntimeError(f"Unsupported conv2d layout {layout}")
elif is_depthwise_conv2d(data.shape, layout, kernel.shape, kernel_layout,
groups):
if layout == "NCHW":
assert kernel_layout == "OIHW"
@@ -126,7 +126,7 @@ def conv2d_strategy_hls(attrs, inputs, out_type, target):
name="depthwise_nhwc.hls",
)
else:
- raise RuntimeError("Unsupported depthwise_conv2d layout
{}".format(layout))
+ raise RuntimeError(f"Unsupported depthwise_conv2d layout {layout}")
else: # group_conv2d
raise RuntimeError("group_conv2d is not supported for hls")
return strategy
@@ -192,5 +192,5 @@ def bitserial_conv2d_strategy_hls(attrs, inputs, out_type,
target):
name="bitserial_conv2d_nhwc.hls",
)
else:
- raise ValueError("Data layout {} not supported.".format(layout))
+ raise ValueError(f"Data layout {layout} not supported.")
return strategy
diff --git a/python/tvm/relay/op/strategy/intel_graphics.py
b/python/tvm/relay/op/strategy/intel_graphics.py
index 115a711144..4bbafb62f2 100644
--- a/python/tvm/relay/op/strategy/intel_graphics.py
+++ b/python/tvm/relay/op/strategy/intel_graphics.py
@@ -52,7 +52,7 @@ def conv2d_strategy_intel_graphics(attrs, inputs, out_type,
target):
plevel=5,
)
else:
- raise RuntimeError("Unsupported conv2d layout {} for intel
graphics".format(layout))
+ raise RuntimeError(f"Unsupported conv2d layout {layout} for intel
graphics")
elif is_depthwise_conv2d(data.shape, layout, kernel.shape, kernel_layout,
groups):
if layout == "NCHW":
assert kernel_layout == "OIHW"
@@ -62,7 +62,7 @@ def conv2d_strategy_intel_graphics(attrs, inputs, out_type,
target):
name="depthwise_conv2d_nchw.intel_graphics",
)
else:
- raise RuntimeError("Unsupported depthwise_conv2d layout
{}".format(layout))
+ raise RuntimeError(f"Unsupported depthwise_conv2d layout {layout}")
else: # group_conv2d
raise RuntimeError("group_conv2d is not supported for intel graphics")
return strategy
diff --git a/python/tvm/relay/op/strategy/mali.py
b/python/tvm/relay/op/strategy/mali.py
index c39487b16d..f37071c9fc 100644
--- a/python/tvm/relay/op/strategy/mali.py
+++ b/python/tvm/relay/op/strategy/mali.py
@@ -70,9 +70,7 @@ def conv2d_strategy_mali(attrs, inputs, out_type, target):
name="conv2d_nchw_spatial_pack.mali",
)
else:
- raise RuntimeError(
- "Unsupported weight layout {} for conv2d
NCHW".format(kernel_layout)
- )
+ raise RuntimeError(f"Unsupported weight layout {kernel_layout}
for conv2d NCHW")
elif layout == "NHWC":
assert kernel_layout == "HWIO"
need_auto_scheduler_layout = is_auto_scheduler_enabled()
@@ -133,7 +131,7 @@ def conv2d_strategy_mali(attrs, inputs, out_type, target):
)
else:
- raise RuntimeError("Unsupported conv2d layout {} for
mali".format(layout))
+ raise RuntimeError(f"Unsupported conv2d layout {layout} for mali")
elif is_depthwise_conv2d(data.shape, layout, kernel.shape, kernel_layout,
groups):
if layout == "NCHW":
assert kernel_layout == "OIHW"
@@ -163,7 +161,7 @@ def conv2d_strategy_mali(attrs, inputs, out_type, target):
name="depthwise_conv2d_nhwc.mali",
)
else:
- raise RuntimeError("Unsupported depthwise_conv2d layout {} for
mali".format(layout))
+ raise RuntimeError(f"Unsupported depthwise_conv2d layout {layout}
for mali")
else: # group_conv2d
raise RuntimeError("group_conv2d is not supported for mali")
return strategy
@@ -207,9 +205,7 @@ def
conv2d_winograd_without_weight_transform_strategy_mali(attrs, inputs, out_ty
"Winograd conv2d NHWC is not enabled for mali without
auto_scheduler."
)
else:
- raise RuntimeError(
- "Unsupported conv2d_winograd_without_weight_transform layout
{}".format(layout)
- )
+ raise RuntimeError(f"Unsupported
conv2d_winograd_without_weight_transform layout {layout}")
return strategy
diff --git a/python/tvm/relay/op/strategy/x86.py
b/python/tvm/relay/op/strategy/x86.py
index bcc9ca4e20..1b69c7a6ca 100644
--- a/python/tvm/relay/op/strategy/x86.py
+++ b/python/tvm/relay/op/strategy/x86.py
@@ -201,7 +201,7 @@ def conv2d_strategy_cpu(attrs, inputs, out_type, target):
name="conv2d_hwcn.generic",
)
else:
- raise RuntimeError("Unsupported conv2d layout {} for
x86".format(layout))
+ raise RuntimeError(f"Unsupported conv2d layout {layout} for x86")
elif is_depthwise_conv2d(data.shape, layout, kernel.shape, kernel_layout,
groups):
if layout == "NCHW":
assert kernel_layout == "OIHW"
@@ -236,7 +236,7 @@ def conv2d_strategy_cpu(attrs, inputs, out_type, target):
name="depthwise_conv2d_nhwc.generic",
)
else:
- raise RuntimeError("Unsupported depthwise_conv2d layout
{}".format(layout))
+ raise RuntimeError(f"Unsupported depthwise_conv2d layout {layout}")
else: # group_conv2d
if layout == "NCHW":
assert kernel_layout == "OIHW"
@@ -258,7 +258,7 @@ def conv2d_strategy_cpu(attrs, inputs, out_type, target):
assert _OIHWio_matcher.match(kernel_layout) # check if kernel is
OIHWio
return conv2d_NCHWc_strategy_cpu(attrs, inputs, out_type, target)
else:
- raise RuntimeError("Unsupported group_conv2d layout
{}".format(layout))
+ raise RuntimeError(f"Unsupported group_conv2d layout {layout}")
return strategy
@@ -352,9 +352,7 @@ def conv3d_strategy_cpu(attrs, inputs, out_type, target):
# or packed layouts.
if layout == "NCDHW":
strategy.add_implementation(
- wrap_compute_conv3d(topi.nn.conv3d_ncdhw),
- naive_schedule,
- name="conv3d_ncdhw.x86",
+ wrap_compute_conv3d(topi.nn.conv3d_ncdhw), naive_schedule,
name="conv3d_ncdhw.x86"
)
elif layout == "NDHWC":
strategy.add_implementation(
@@ -367,7 +365,7 @@ def conv3d_strategy_cpu(attrs, inputs, out_type, target):
name="conv3d_ndhwc.x86",
)
else:
- raise ValueError("Not support this layout {} yet".format(layout))
+ raise ValueError(f"Not support this layout {layout} yet")
else:
# Use autotvm templates
if layout == "NCDHW":
@@ -383,7 +381,7 @@ def conv3d_strategy_cpu(attrs, inputs, out_type, target):
name="conv3d_ndhwc.x86",
)
else:
- raise ValueError("Not support this layout {} yet".format(layout))
+ raise ValueError(f"Not support this layout {layout} yet")
return strategy
@@ -410,7 +408,7 @@ def conv1d_strategy_cpu(attrs, inputs, out_type, target):
name="conv1d_nwc.x86",
)
else:
- raise ValueError("Unsupported conv1d layout {}".format(layout))
+ raise ValueError(f"Unsupported conv1d layout {layout}")
else:
if layout == "NCW":
strategy.add_implementation(
@@ -425,7 +423,7 @@ def conv1d_strategy_cpu(attrs, inputs, out_type, target):
name="group_conv1d_nwc.x86",
)
else:
- raise ValueError("Unsupported conv1d layout {}".format(layout))
+ raise ValueError(f"Unsupported conv1d layout {layout}")
return strategy
@@ -500,9 +498,7 @@ def matmul_strategy_cpu(attrs, inputs, out_type, target):
"Recommend to use cblas/mkl/dnnl for better performance."
)
strategy.add_implementation(
- wrap_compute_matmul(topi.nn.matmul),
- naive_schedule,
- name="matmul.generic",
+ wrap_compute_matmul(topi.nn.matmul), naive_schedule,
name="matmul.generic"
)
return strategy
@@ -750,7 +746,7 @@ def bitserial_conv2d_strategy_cpu(attrs, inputs, out_type,
target):
name="bitserial_conv2d_nhwc.x86",
)
else:
- raise ValueError("Data layout {} not supported.".format(layout))
+ raise ValueError(f"Data layout {layout} not supported.")
return strategy
@@ -816,9 +812,7 @@ def
conv2d_winograd_without_weight_transform_strategy_cpu(attrs, inputs, out_typ
else:
raise RuntimeError("Both AutoScheduler and MetaSchedule are not
enabled")
else:
- raise RuntimeError(
- "Unsupported conv2d_winograd_without_weight_transform layout
{}".format(layout)
- )
+ raise RuntimeError(f"Unsupported
conv2d_winograd_without_weight_transform layout {layout}")
return strategy
diff --git a/python/tvm/relay/op/tensor.py b/python/tvm/relay/op/tensor.py
index aa3ede5a07..6b488719eb 100644
--- a/python/tvm/relay/op/tensor.py
+++ b/python/tvm/relay/op/tensor.py
@@ -32,7 +32,7 @@ def _make_virtual_device(device):
return target.VirtualDevice(device)
if isinstance(device, str):
return target.VirtualDevice(_nd.device(device))
- raise ValueError("expecting a Device or device name, but received a %s" %
(type(device)))
+ raise ValueError(f"expecting a Device or device name, but received a
{type(device)}")
# We create a wrapper function for each operator in the
diff --git a/python/tvm/relay/op/transform.py b/python/tvm/relay/op/transform.py
index c8e4879a61..ef1cdb3afd 100644
--- a/python/tvm/relay/op/transform.py
+++ b/python/tvm/relay/op/transform.py
@@ -235,7 +235,7 @@ def squeeze(data, axis=None):
try:
tempaxis.append(int(tmpax))
except ValueError as err:
- raise RuntimeError("Unrecognized axis type: %s" % err)
+ raise RuntimeError(f"Unrecognized axis type: {err}")
axis = tempaxis
return _make.squeeze(data, axis)
@@ -324,7 +324,7 @@ def reshape(data, newshape, allowzero=False):
try:
tempshape.append(int(shape))
except ValueError as err:
- raise RuntimeError("Unrecognized shape type: %s" % err)
+ raise RuntimeError(f"Unrecognized shape type: {err}")
newshape = tempshape
return _make.reshape(data, list(newshape), allowzero)
diff --git a/python/tvm/relay/op/vision/_rcnn.py
b/python/tvm/relay/op/vision/_rcnn.py
index 4686974059..a3f749236d 100644
--- a/python/tvm/relay/op/vision/_rcnn.py
+++ b/python/tvm/relay/op/vision/_rcnn.py
@@ -66,7 +66,7 @@ def convert_roi_align(attrs, inputs, tinfos, desired_layouts):
if desired_data_layout in ["NCHW", "NHWC"]:
return relay.vision.roi_align(data, rois, **new_attrs)
- raise ValueError("Layout %s is not yet supported." % desired_data_layout)
+ raise ValueError(f"Layout {desired_data_layout} is not yet supported.")
@reg.register_convert_op_layout("vision.roi_pool")
@@ -108,7 +108,7 @@ def convert_roi_pool(attrs, inputs, tinfos,
desired_layouts):
if desired_data_layout in ["NCHW", "NHWC"]:
return relay.vision.roi_pool(data, rois, **new_attrs)
- raise ValueError("Layout %s is not yet supported." % desired_data_layout)
+ raise ValueError(f"Layout {desired_data_layout} is not yet supported.")
# roi_pool
