Files
apache--tvm/python/tvm/script/tir/node.py
T
Ruihang Lai 8813d0a2bd [TVMScript] Parser int64 support (#10789)
## Context

When dealing with end-to-end models, we note that some tensors may have large shapes. Thus, when designing graph-level IR, we sometimes use `int64` instead of `int32` for the shape. Below is an dense GeMM example which has `int64` input tensor shape:

```python
@tvm.script.ir_module
class Module:
    @T.prim_func
    def main(rxplaceholder: T.Buffer[(1, 512), "float32"], rxplaceholder_1: T.Buffer[(T.int64(1000), T.int64(512)), "float32"], T_matmul_NT: T.Buffer[(1, T.int64(1000)), "float32"]) -> None:
        # function attr dict
        T.func_attr({"global_symbol": "dense", "tir.noalias": True, "op_pattern": 3})
        # body
        # with T.block("root")
        for i0_0, i1_0, i0_1, i1_1, i2_0, i0_2, i1_2, i2_1, i0_3, i1_3 in T.grid(1, 4, 1, 25, 8, 1, 10, 64, 1, 1):
            with T.block("T_matmul_NT"):
                i = T.axis.spatial(1, 0)
                j = T.axis.spatial(T.int64(1000), i1_0 * T.int64(250) + i1_1 * T.int64(10) + i1_2)
                k = T.axis.reduce(512, i2_0 * 64 + i2_1)
                T.reads(T_matmul_NT[i, j], rxplaceholder[i, k], rxplaceholder_1[j, k])
                T.writes(T_matmul_NT[i, j])
                T.block_attr({"layout_free_placeholders":[rxplaceholder_1], "meta_schedule.tiling_structure":"SSRSRS"})
                with T.init():
                    T_matmul_NT[i, j] = T.float32(0)
                T_matmul_NT[i, j] = T_matmul_NT[i, j] + rxplaceholder[i, k] * rxplaceholder_1[j, k]
```

## Problem

Though our TVMScript printer can easily print `int64` constants, the parser had poor support for `int64`. So this PR introduces some parser support for `int64`, basically about the data type of loop variables, block iterators and block read/write regions.

Besides the parser, most of the TIR schedule primitives didn't take `int64` into account in their implementations. These schedule primitives will be fixed and updated in recent future, in followup PRs.
2022-03-25 15:09:24 -07:00

160 lines
5.5 KiB
Python

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# pylint: disable=redefined-builtin
"""TVM Script nodes."""
from typing import Optional, Union, List, Callable
import synr
from tvm.runtime import ObjectGeneric, convert
from tvm.tir import PrimExpr, Buffer, BufferLoad
from tvm.ir import Span
class Slice:
"""A helper class to present slice information for BufferSlice
Parameters
----------
start : Union[PrimExpr, int]
The start index.
stop : Optional[Union[PrimExpr, int]]
The stop index, None means the Slice is an element-wise index
span : Optional[Span]
The location of the slice in the source.
"""
start: Union[PrimExpr, int]
stop: Optional[Union[PrimExpr, int]]
span: Optional[Span]
def __init__(
self,
start: Union[PrimExpr, int],
stop: Optional[Union[PrimExpr, int]] = None,
span: Optional[Span] = None,
):
self.start = start
self.stop = stop
self.span = span
class BufferSlice(ObjectGeneric):
"""A generic object for representing general buffer access. Following cases are supported:
- element wise access buffer[i, j], which can be converted to BufferLoad if necessary
- slice access buffer[i: i + 1, j : j + 2]
- union of element and slice buffer[i, j: j + 2]
This node is used in TVMScript to parse BufferLoad, BufferRegion and Realize
Parameters
----------
buffer : Buffer
The buffer.
indices : List[Union[Slice, PrimExpr, int]]
The access indexes can be slice, PrimExpr or int.
report_error: Callable[[str, Union[Span, synr.ast.Span]], None]
The error report func
span : Optional[Span]
The location of the buffer access in the source.
"""
buffer: Buffer
slices: List[Slice]
report_error: Callable[[str, Union[Span, synr.ast.Span]], None]
span: Optional[Span]
def __init__(
self,
buffer: Buffer,
indices: List[Union[Slice, PrimExpr, int]],
report_error: Callable[[str, Union[Span, synr.ast.Span]], None],
span: Optional[Span] = None,
):
def check_index(index: Union[int, PrimExpr]):
"""Check input index is non-negative integer or PrimExpr"""
if isinstance(index, int):
if index < 0:
report_error("Negative index is not allowed during buffer access", span)
elif isinstance(index, PrimExpr):
element_dtype = index.dtype.split("x", maxsplit=1)[0]
if element_dtype[:3] != "int":
report_error(
"index expected an integer type PrimExpr but got " + str(index.dtype),
index.span,
)
else:
report_error(
"Unsupported index type, expected int or tvm.tir.PrimExpr, but got "
+ str(type(index)),
span,
)
slices: List[Union[Slice, BufferSlice]] = []
for index in indices:
if isinstance(index, Slice):
index.start, index.stop = [convert(_) for _ in [index.start, index.stop]]
check_index(index.start)
check_index(index.stop)
slices.append(index)
elif isinstance(index, (PrimExpr, int)):
check_index(index)
slices.append(Slice(index))
elif isinstance(index, BufferSlice):
buffer_load = index.asobject()
check_index(buffer_load)
slices.append(Slice(buffer_load))
else:
report_error(
"Unsupported index type for BufferSlice, "
+ "expected int, tvm.tir.PrimExpr, tvm.tir.Slice, but got "
+ str(type(index)),
span,
)
self.buffer = buffer
self.slices = slices
self.report_error = report_error
self.span = span
def __str__(self):
regions: List[str] = []
for s in self.slices:
if s.stop is None:
regions.append(str(s.start))
else:
regions.append(str(s.start) + ": " + str(s.stop))
return self.buffer.name + "[" + ", ".join(regions) + "]"
def asobject(self) -> BufferLoad:
"""Convert object."""
for s in self.slices:
if s.stop is not None:
self.report_error("BufferLoad only accepts elementwise access", self.span)
indices = [s.start for s in self.slices]
return BufferLoad(self.buffer, indices, span=self.span)
def astype(self, dtype: str, span: Optional[Span] = None) -> PrimExpr:
return self.asobject().astype(dtype, span)