masahi’s gists

masahi / tune_larq_icelake.py

Last active December 14, 2020 05:41

	import tvm
	from tvm import relay, autotvm
	import larq_zoo
	import numpy as np
	# import tvm.contrib.graph_runtime as runtime

	import tvm.contrib.debugger.debug_runtime as runtime
	import tvm.relay.testing
	from tvm.autotvm.tuner import RandomTuner

masahi / tune_conv2d_nchw16c.py

Created December 11, 2020 07:48

	import logging
	import sys

	import numpy as np
	import tvm
	import tvm.topi.testing
	from tvm import te, testing
	from tvm.topi.utils import get_const_tuple
	from tvm import autotvm, topi

masahi / tune_conv2d_vpopcount.py

Last active December 14, 2020 00:39

	import logging
	import sys

	import numpy as np
	import tvm
	import tvm.topi.testing
	from tvm import te, testing
	from tvm.topi.utils import get_const_tuple
	from tvm import autotvm, topi

masahi / dense_tuning_rocm.txt

Created December 7, 2020 07:59

	Computational DAG:
	data = PLACEHOLDER [1, 2048]
	weight = PLACEHOLDER [1000, 2048]
	T_dense(i, j) += (data[i, k]*weight[j, k])
	bias = PLACEHOLDER [1000]
	T_add(i, j) = (T_dense[i, j] + bias[j])

	----------------------------------------------------------------------
	------------------------------ [ Search ]
	----------------------------------------------------------------------

masahi / mobilenet_v2_x86.log

Created April 23, 2020 07:08

{"input": ["llvm -device=arm_cpu -target=aarch64-unknown-linux-gnu -mattr=+neon", "depthwise_conv2d_NCHWc.x86", [["TENSOR", [1, 576, 16, 16], "int16"], ["TENSOR", [576, 1, 3, 3], "int16"], [1, 1], [0, 0, 0, 0], [1, 1], "NCHW", "NCHW", "int32"], {}], "config": {"index": 948, "code_hash": null, "entity": [["tile_ic", "sp", [-1, 4]], ["tile_oc", "sp", [-1, 4]], ["tile_ow", "sp", [-1, 7]], ["unroll_kw", "ot", true]]}, "result": [[0.000205725], 0, 0.3024606704711914, 1587601624.52548], "version": 0.2, "tvm_version": "0.7.dev1"}

{"input": ["llvm -device=arm_cpu -target=aarch64-unknown-linux-gnu -mattr=+neon", "depthwise_conv2d_NCHWc.x86", [["TENSOR", [1, 192, 30, 30], "int16"], ["TENSOR", [192, 1, 3, 3], "int16"], [1, 1], [0, 0, 0, 0], [1, 1], "NCHW", "NCHW", "int32"], {}], "config": {"index": 572, "code_hash": null, "entity": [["tile_ic", "sp", [-1, 96]], ["tile_oc", "sp", [-1, 96]], ["tile_ow", "sp", [-1, 4]], ["unroll_kw", "ot", true]]}, "result": [[0.0002175626], 0, 3.8473615646362305, 1587602877.3487854], "ver

masahi / ocaml-asp_merlin

Created April 17, 2020 01:58

	B _build/lib/
	B _build/lib_test/
	B _build/benchmarks/*
	B /home/masa/.opam/4.07.1+BER/lib/asp/
	B /home/masa/.opam/4.07.1+BER/lib/letrec/
	CMT /home/masa/projects/languages/ocaml/research/metaocaml/yallop/metaocaml-letrec/_build/lib
	B /home/masa/projects/languages/ocaml/research/metaocaml/yallop/metaocaml-letrec/_build/lib
	S /home/masa/projects/languages/ocaml/research/metaocaml/yallop/metaocaml-letrec/lib
	S lib
	S lib_test

masahi / letrec_merlin

Created April 17, 2020 01:57

	B _build/lib/
	B _build/lib_test/
	B /home/masa/.opam/4.07.1+BER/lib/letrec/
	CMT /home/masa/.opam/4.07.1+BER/lib/ocaml/compiler-libs
	B /home/masa/.opam/4.07.1+BER/lib/ocaml/compiler-libs
	S lib
	S lib_test
	EXT meta
	PKG delimcc
	FLG -open Trx

masahi / stacked_bidir.txt

Created April 11, 2020 08:20

fn (%v54: Tensor[(16, 3), float32], %v60: Tensor[(16), float32], %v61: Tensor[(16), float32], %v66: Tensor[(16, 4), float32], %v72: Tensor[(16), float32], %v73: Tensor[(16), float32], %v94: Tensor[(4), float32], %v95: Tensor[(4), float32], %states: List[List[(Tensor[(2, 4), float32], Tensor[(2, 4), float32])]], %input: Tensor[(5, 2, 3), float32], %v135: Tensor[(16, 3), float32], %v141: Tensor[(16), float32], %v142: Tensor[(16), float32], %v147: Tensor[(16, 4), float32], %v153: Tensor[(16), float32], %v154: Tensor[(16), float32], %v175: Tensor[(4), float32], %v176: Tensor[(4), float32], %v222: Tensor[(16, 4), float32], %v228: Tensor[(16), float32], %v229: Tensor[(16), float32], %v234: Tensor[(16, 4), float32], %v240: Tensor[(16), float32], %v241: Tensor[(16), float32], %v262: Tensor[(4), float32], %v263: Tensor[(4), float32], %v303: Tensor[(16, 4), float32], %v309: Tensor[(16), float32], %v310: Tensor[(16), float32], %v315: Tensor[(16, 4), float32], %v321: Tensor[(16), float32], %v322: Tensor[(16), float32], %

masahi / bidir_lstm.txt

Last active April 11, 2020 04:15

	fn (%v45: Tensor[(16, 3), float32], %v51: Tensor[(16), float32], %v52: Tensor[(16), float32], %v57: Tensor[(16, 4), float32], %v63: Tensor[(16), float32], %v64: Tensor[(16), float32], %v85: Tensor[(4), float32], %v86: Tensor[(4), float32], %states: List[(Tensor[(2, 4), float32], Tensor[(2, 4), float32])], %input: Tensor[(5, 2, 3), float32], %v119: Tensor[(16, 3), float32], %v125: Tensor[(16), float32], %v126: Tensor[(16), float32], %v131: Tensor[(16, 4), float32], %v137: Tensor[(16), float32], %v138: Tensor[(16), float32], %v159: Tensor[(4), float32], %v160: Tensor[(4), float32]) -> (Tensor[(?, 2, ?), float32], List[(Tensor[(2, 4), float32], Tensor[(2, 4), float32])]) {
	%0 = Nil /* ty=List[Tensor[(?, 2, ?), float32]] */;
	%1 = Nil /* ty=List[Tensor[(2, 4), float32]] */;
	%2 = @nth(%states, 0 /* ty=int32 /) / ty=(Tensor[(2, 4), float32], Tensor[(2, 4), float32]) */;
	%38 = (
	let %while_loop: fn (int32, List[Tensor[(2, 4), float32]], (Tensor[(2, 4), float32], Tensor[(2, 4), float32]), Tensor[(5, 2, 3

masahi / stacked_lstm_torchscript.txt

Created April 9, 2020 22:50

	ANTLR runtime and generated code versions disagree: 4.8!=4.7.2
	ANTLR runtime and generated code versions disagree: 4.8!=4.7.2
	graph(%self : __torch__.custom_lstms.StackedLSTM,
	%input.1 : Tensor,
	%states.1 : (Tensor, Tensor)[]):
	%i.2 : int = prim::Constant[value=0]() # /home/masa/projects/dev/torchscript-to-tvm/custom_lstms.py:80:8
	%i.3 : int = prim::Constant[value=1]() # /home/masa/projects/dev/torchscript-to-tvm/custom_lstms.py:80:8
	%output_states.1 : (Tensor, Tensor)[] = prim::ListConstruct()
	%6 : __torch__.torch.nn.modules.container.ModuleList = prim::GetAttr[name="layers"](%self)
	%7 : __torch__.custom_lstms.LSTMLayer = prim::GetAttr[name="0"](%6)