wanchaol’s gists

wanchaol / gist:a9c2397f11d7a5e5d8e3b8e0bffefff6

Created February 22, 2019 22:25

	Benchmarking LSTMs...
	name avg_fwd std_fwd avg_bwd std_bwd
	cudnn_layernorm 32.71 0.7494 10.43 0.08965
	jit_layernorm 41.25 0.7082 98.66 2.56
	jit_layernorm_de 34.41 0.7501 113.3 1.037

wanchaol / bm.py

Created March 18, 2019 23:59

	import torch
	import torch.nn as nn
	from torch.jit import ScriptModule, script_method
	from typing import List


	class BatchNorm(ScriptModule):
	__constants__ = ['mom', 'eps']

	def __init__(self, nf, mom=0.9, eps=1e-5):

wanchaol / test_bm.md

Last active March 19, 2019 20:30

import torch
import torch.nn as nn
from torch.jit import ScriptModule, script_method
from typing import List


class BatchNormList(ScriptModule):
    __constants__ = ['mom', 'eps']

wanchaol / gist:1630385e1aca100ca1a084820f68c5a2

Created March 29, 2019 23:20

	--
	-- ****** Summary ******
	-- General:
	-- CMake version : 3.12.2
	-- CMake command : /private/home/wanchaol/.conda/envs/pt/bin/cmake
	-- System : Linux
	-- C++ compiler : /scratch/wanchaol/ccache/lib/c++
	-- C++ compiler id : GNU
	-- C++ compiler version : 7.3.0
	-- BLAS : MKL

wanchaol / gist:1501e4b225d2c82226cdb981cabd7f65

Created April 1, 2019 06:25

	graph(%input.1 : Float(, ),
	%weight.1 : Float(, ),
	%bias.1 : Float(*),
	%weight.2 : Float(, ),
	%bias.2 : Float(*),
	%weight.3 : Float(, ),
	%bias.3 : Float(*),
	%weight.4 : Float(, ),
	%bias.4 : Float(*),
	%weight.5 : Float(, ),

wanchaol / gist:1afcbbef8b9efad10bbda8d2802868ff

Created April 12, 2019 18:22

lstmcelll_forward

	graph(%x : Float(, ),
	%hx : Float(, ),
	%cx : Float(, ),
	%w_ih : Float(, ),
	%w_hh : Float(, ),
	%b_ih : Float(*),
	%b_hh : Float(*)):
	%hy : Float(, ), %cy : Float(, ) = prim::DifferentiableGraph_0(%cx, %b_hh, %b_ih, %hx, %w_hh, %x, %w_ih)
	%30 : (Float(, ), Float(, )) = prim::TupleConstruct(%hy, %cy)
	return (%30)

wanchaol / gist:ded928ba77c4703e41fa1e681172bec5

Created April 12, 2019 18:27

lstmcell_forward_unoptimized

	graph(%x : Float(, ),
	%hx : Float(, ),
	%cx : Float(, ),
	%w_ih : Float(, ),
	%w_hh : Float(, ),
	%b_ih : Float(*),
	%b_hh : Float(*)):
	%hy : Float(, ), %cy : Float(, ) = prim::DifferentiableGraph_0(%cx, %b_hh, %b_ih, %hx, %w_hh, %x, %w_ih)
	%30 : (Float(, ), Float(, )) = prim::TupleConstruct(%hy, %cy)
	return (%30)

wanchaol / gist:0e02974f23f2bb58ae20e0293bed830e

Created April 25, 2019 17:54

	======================================================================
	ERROR: test_max_pool2d (__main__.TestOperators)
	----------------------------------------------------------------------
	Traceback (most recent call last):
	File "test/test_operators.py", line 148, in test_max_pool2d
	max_pool2d(X)
	File "/data/users/wanchaol/pytorch/torch/nn/modules/module.py", line 493, in __call__
	result = self.forward(input, *kwargs)
	RuntimeError: [10:54:24] /home/wanchaol/local/tvm/src/relay/ir/error.cc:131:
	Error(s) have occurred. We have annotated the program with them:

wanchaol / gist:bb44846d4fcbf6447152a79a6b666c0c

Created April 26, 2019 18:16

	@torch.jit.script
	def test_if_refinement(weight, bias):
	# type: (Optional[Tensor], Optional[Tensor]) -> Tuple[Optional[int], Optional[int]]
	if weight is not None and bias is not None:
	grad_weight = 1
	grad_bias = 2
	elif weight is not None:
	grad_weight = 2
	grad_bias = None
	elif bias is not None:

wanchaol / gist:c50875569d4266aff20133b6d0f387c3

Last active April 29, 2019 05:00

	import torch
	import torch.nn.functional as F
	import torch.jit as jit
	from torch import Tensor


	@jit.script
	def test_mm_back(input1, input2, normalized_shape):
	# type: (Tensor, Tensor, List[int]) -> Tensor
	return F.layer_norm(torch.mm(input1, input2), normalized_shape)

	graph(%input.1 : Float(, ),
	%weight.1 : Float(, ),
	%bias.1 : Float(*),
	%weight.2 : Float(, ),
	%bias.2 : Float(*),
	%weight.3 : Float(, ),
	%bias.3 : Float(*),
	%weight.4 : Float(, ),
	%bias.4 : Float(*),
	%weight.5 : Float(, ),

	graph(%x : Float(, ),
	%hx : Float(, ),
	%cx : Float(, ),
	%w_ih : Float(, ),
	%w_hh : Float(, ),
	%b_ih : Float(*),
	%b_hh : Float(*)):
	%hy : Float(, ), %cy : Float(, ) = prim::DifferentiableGraph_0(%cx, %b_hh, %b_ih, %hx, %w_hh, %x, %w_ih)
	%30 : (Float(, ), Float(, )) = prim::TupleConstruct(%hy, %cy)
	return (%30)

	graph(%x : Float(, ),
	%hx : Float(, ),
	%cx : Float(, ),
	%w_ih : Float(, ),
	%w_hh : Float(, ),
	%b_ih : Float(*),
	%b_hh : Float(*)):
	%hy : Float(, ), %cy : Float(, ) = prim::DifferentiableGraph_0(%cx, %b_hh, %b_ih, %hx, %w_hh, %x, %w_ih)
	%30 : (Float(, ), Float(, )) = prim::TupleConstruct(%hy, %cy)
	return (%30)

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