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@benvanik
benvanik / 0-input.mlir
Created May 12, 2020 23:22
resnet50 IR
module attributes {tf.versions = {bad_consumers = [], min_consumer = 12 : i32, producer = 370 : i32}} {
flow.variable @"__iree_flow___sm_node186__m.layer-2.kernel" dense<1.200000e+00> : tensor<7x7x3x64xf32> attributes {sym_visibility = "private"}
flow.variable @"__iree_flow___sm_node187__m.layer-2.bias" dense<0.000000e+00> : tensor<64xf32> attributes {sym_visibility = "private"}
flow.variable @"__iree_flow___sm_node193__m.layer-3.gamma" dense<1.000000e+00> : tensor<64xf32> attributes {sym_visibility = "private"}
flow.variable @"__iree_flow___sm_node194__m.layer-3.beta" dense<0.000000e+00> : tensor<64xf32> attributes {sym_visibility = "private"}
flow.variable @"__iree_flow___sm_node195__m.layer-3.moving_mean" dense<0.000000e+00> : tensor<64xf32> attributes {sym_visibility = "private"}
flow.variable @"__iree_flow___sm_node196__m.layer-3.moving_variance" dense<1.000000e+00> : tensor<64xf32> attributes {sym_visibility = "private"}
flow.variable @"__iree_flow___sm_node213__m.layer-7.kernel" dense<1.2
@benvanik
benvanik / 0-input.mlir
Last active April 9, 2020 05:18
simple_mul target-specific interface
module {
func @simple_mul(%arg0: tensor<4xf32>, %arg1: tensor<4xf32>) -> tensor<4xf32> attributes {iree.module.export} {
%0 = xla_hlo.multiply %arg0, %arg1 {name = "mul.1"} : tensor<4xf32>
return %0 : tensor<4xf32>
}
}
def HAL_DeviceSwitchOp : HAL_Op<"device.switch"> {
let summary = [{runtime device switch pseudo op}];
let description = [{
Switches between multiple regions based on the runtime device type.
The provided regions are pattern-matched against the runtime backend of the
given device and executed only when the device matches.
As the patterns can match on wildcards this enables conditions that have
similar bodies to be folded. The patterns themselves are only matched once
at startup and then the results are cached; the runtime overhead is
hal.executable @simpleMath_ex_dispatch_0 {
hal.interface @legacy_io {
hal.interface.binding @arg0, set=0, binding=0, type="StorageBuffer", access="Read"
hal.interface.binding @ret0, set=0, binding=1, type="StorageBuffer", access="Write|Discard"
}
hal.executable.entry_point @simpleMath_rgn_dispatch_0 attributes {interface = @legacy_io, ordinal = 0 : i32, signature = (tensor<4xf32>) -> tensor<4xf32>, workgroup_size = dense<[32, 1, 1]> : vector<3xi32>}
hal.executable.binary attributes {data = dense<"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
@benvanik
benvanik / endtoend_hal_ops.mlir
Created January 21, 2020 21:54
IREE HLO -> flatbuffer end-to-end example dump
*** IR Dump After Canonicalizer ***
module @hal_usage {
func @hloElementwiseOps(%arg0: tensor<4xf32>) -> tensor<4xf32> attributes {iree.module.export} {
%0 = xla_hlo.add %arg0, %arg0 : tensor<4xf32>
%1 = xla_hlo.sub %0, %arg0 : tensor<4xf32>
%2 = xla_hlo.mul %1, %arg0 : tensor<4xf32>
return %2 : tensor<4xf32>
}
// Copyright 2019 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
@benvanik
benvanik / BUILD
Last active July 18, 2017 14:58
bzlrepro
package(default_visibility = ["//visibility:public"])
cc_library(
name = "a",
srcs = ["a.cc"],
hdrs = ["a.h"],
)
cc_library(
name = "b",
/* 0.0 */ exec
/* 3 */ vfetch_full r1.xyz1, r0.x, vf95, DataFormat=FMT_32_32_32_FLOAT, Stride=7, Signed=true, NumFormat=integer, PrefetchCount=7
/* 4 */ vfetch_mini r0, Offset=3, DataFormat=FMT_32_32_32_32_FLOAT, Signed=true, NumFormat=integer
/* 0.1 */ alloc interpolators
/* 1.0 */ exec
/* 5 */ max o0, r0, r0
/* 1.1 */ alloc position
/* 2.0 */ exec
/* 6 */ max oPos, r1, r1
/* 2.1 */ exece
SPIR-V 1.0:
Glslang Reference Front End from Khronos (Contact John Kessenich, johnkessenich@google.com) - version 0x0001
IDs up to {204}
Source is GLSL 450
Capabilities: Geometry GeometryPointSize ClipDistance Unrecognised{54}
Entry point 'main' (Geometry Shader)
Triangles