Source

bllip-parser / Makefile.gavper

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
# 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
#
#     http://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, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.  See the
# License for the specific language governing permissions and limitations
# under the License.

# Top-level makefile for reranking parser
# Mark Johnson, 24th October 2007

########################################################################
#                                                                      #
#                                Summary                               #
#                                                                      #
########################################################################
#
# To build just the reranking parser run-time, execute:
#
# make                 # builds reranking parser programs
#
# To retrain the reranking parser, run the following steps:
#
# make reranker        # builds reranking parser and training programs
# make nbesttrain      # builds 20 folds of n-best training parses
# make eval-reranker   # extracts features, estimates weights, and evaluates
#
# The following high-level goals may also be useful:
#
# make nbestrain-clean # removes temporary files used in nbesttrain
# make nbest-oracle    # oracle evaluation of n-best results 
# make features        # extracts features from 20-fold parses
# make train-reranker  # trains reranker model
# make train-clean     # removes all temporary files used in training
#
# I typically run nbesttrain to produce the n-best parses 

# To run 2 jobs in parallel (e.g. on a multiprocessor) run, e.g.,
#
# make -j 2 nbesttrain
#
# This really only helps with nbesttrain, since the other time consuming
# step (reranker feature weight estimation) isn't yet parallelized.

# The environment variable GCCFLAGS can be used to specify
# machine-dependent optimization flags, e.g.
#
# setenv GCCFLAGS "-march=pentium4"
#
# or
#
# setenv GCCFLAGS "-march=opteron -m64"
#
# The top-level make goal builds the reranking parser using a pre-trained
# model.  To build this parser, just run
#
# make 
#
# You may need to tweak the following variables to suit your environment

# GCCFLAGS is not set here, so we use the shell environment
# variable's value.  But you can set it here if you want.
# Version 4.1 and later gcc permit -march=native, but older
# versions will need -march=pentium4 or -march=opteron
#
# GCCFLAGS = -march=native -mfpmath=sse -msse2 -mmmx -I <path-to-boost-libraries>

# CFLAGS is used for all C and C++ compilation
#
CFLAGS = -MMD -O6 -Wall -ffast-math -finline-functions -fomit-frame-pointer -fstrict-aliasing $(GCCFLAGS)

# for debugging, uncomment the following CFLAGS and LDFLAGS
#
# CFLAGS = -g -O -MMD -Wall -ffast-math -fstrict-aliasing $(GCCFLAGS)
# LDFLAGS = -g -Wall


# Building the 20-fold training data with nbesttrain 
# --------------------------------------------------

# For training the parser and reranker you will need your own copy of the
# Penn WSJ Treebank.
#
# PENNWSJTREEBANK must be set to the base directory of the Penn WSJ Treebank
#
PENNWSJTREEBANK=/usr/local/data/Penn3/parsed/mrg/wsj/

# NPARSES is the number of alternative parses to consider for each sentence
#
NPARSES=50

# NFOLDS is the number of folds to use, and FOLDS is a list of the numbers
# from 00 to NFOLDS-1 (I couldn't see how to program this in make).
#
NFOLDS=20
FOLDS=00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19

# SECTIONS is a list of sections from the treebank to n-best parse
# using Eugene's standard n-best parser (in addition to the folds).
#
SECTIONS=22 23 24

# NBESTPARSER is the n-best parser.  If you change this, please
# change NBESTPARSERNICKNAME below as well.
#
NBESTPARSER=first-stage/PARSE/parseIt

# NBESTTRAINER is the program (probably a shell script) for training
# the n-best parser.  If you change this, please change
# NBESTPARSERNICKNAME below as well.
#
NBESTTRAINER=first-stage/TRAIN/trainParser

# NBESTPARSERNICKNAME is a nickname for the n-best parser.  If you 
# experiment with several n-best parsers, give each one a different
# nickname.
#
PARSERNICKNAME=ec

# TMP specifies a temporary directory used while constructing the
# folds while producing the training parses for the reranker.  You can
# delete this directory after nbesttrain has finished.  On an NFS
# system you may want to change this to a local directory.
#
TMP=tmp

# Extracting features from 20-fold n-best parses
# ----------------------------------------------

# VERSION should be either "final" or "nonfinal".  If VERSION is
# "nonfinal" then we train on folds 00-19, folds 20-21 are used as
# dev, and sections 22 and 24 are used as test1 and test2
# respectively.  If VERSION is "final" then we train on folds 00-21,
# section 24 is used as dev and sections 22 and 23 are used as test1
# and test2 respectively.
#
VERSION=nonfinal
# VERSION=final

# FEATUREEXTRACTOR is the program that used to extract features from
# the 20-fold n-best parses.  If you change this, please pick a new 
# FEATURESNICKNAME below.
#
FEATUREEXTRACTOR=second-stage/programs/features/extract-spfeatures

# FEATUREEXTRACTORFLAGS are flags you want to give to the feature extractor
#
FEATUREEXTRACTORFLAGS=-l -c -i -s 5

# FEATURESNICKNAME is an arbitrary string used to identify a
# particular set of extracted features for training the reranker.  You
# can keep several different sets of feature counts and corresponding
# models around by giving each a unique FEATURESNICKNAME.  If you
# develop a new set of features, give them a new FEATURESNICKNAME so
# they doesn't over-write the existing features.
#
FEATURESNICKNAME=sp

# Estimating weights for features
# -------------------------------

# ESTIMATOR is the program used to estimate feature weights from the
# feature counts. This is the feature weight estimator that gives best
# performance.  There are others in the same directory (e.g., weighted
# perceptron).  If you decide to use a different feature weight
# estimator you should also change ESTIMATORNICKNAME below.
#
ESTIMATOR=second-stage/programs/wlle/gavper

# ESTIMATORFLAGS are flags given to the estimator
#
ESTIMATORFLAGS= -a -n 10 -d 10 -F 1 -m 0

# ESTIMATORNICKNAME
#
ESTIMATORNICKNAME=gavper-aa

########################################################################
#
# You probably shouldn't need to change anything below here.

# TARGETS is the list of targets built when make is called
# without arguments
#
TARGETS = PARSE reranker-runtime sparseval

CXXFLAGS = $(CFLAGS)
export CFLAGS
export CXXFLAGS

.PHONY: top
top: $(TARGETS)

# PARSE builds the n-best first-stage parser (i.e., Eugene's parser).
#
.PHONY: PARSE
PARSE:
	make -C first-stage/PARSE parseIt

# TRAIN builds the programs needed to train the first-stage parser.
#
.PHONY: TRAIN
TRAIN:
	make -C first-stage/TRAIN all

# reranker-runtime builds the run-time components of the reranker.
# These include best-parses, which reranks the n-best parses produced
# by the first-stage parser, and ptb, which is a program that converts
# Penn Treebank trees into the various formats needed by Eugene's
# parser, the reranker training programs, sparseval, etc.  
#
.PHONY: reranker-runtime
reranker-runtime:
	make -C second-stage/programs/features best-parses
	make -C second-stage/programs/prepare-data ptb

# reranker builds the training and run-time components of the reranker.
# These include:
#  ptb, which converts the Penn Treebank parse trees into
#       the various formats needed by Eugene's parser, the reranker training
#       program, sparseval, etc., 
#  extract-spfeatures, which produces feature-count files used to train 
#       the reranker, 
#  cvlm, which estimates the feature weights.
#
.PHONY: reranker
reranker: top TRAIN
	make -C second-stage

# EVALB has been replaced with sparseval (nearly the same features with fewer bugs)
#
sparseval: SParseval/src/sparseval

SParseval:
	wget http://old-site.clsp.jhu.edu/ws2005/groups/eventdetect/files/SParseval.tgz
	tar xvzf SParseval.tgz
	rm SParseval.tgz

SParseval/src/sparseval: SParseval
	rm -f SParseval/src/*.o
	$(MAKE) -C SParseval/src sparseval

# clean removes object files.
#
.PHONY: clean
clean:
	(cd first-stage; rm -f PARSE/*.o; rm -f TRAIN/*.o)
	make -C first-stage/TRAIN clean
	make -C first-stage/PARSE clean
	make -C second-stage clean

# nbesttrain-clean removes temporary files used in constructing the 20
# folds of n-best training data.
#
nbesttrain-clean:
	rm -fr $(TMP)

# train-clean gets rid of all data not essential for the reranking
# parser. 
#
.PHONY: train-clean
train-clean: nbesttrain-clean
	rm -fr results
	make -C second-stage train-clean

# real-clean tries to get rid of all object and binary files to
# produce a version for distribution.  But Eugene writes new programs
# faster than I can make real-clean clean them up!
#
.PHONY: real-clean
real-clean: clean train-clean
	(cd first-stage; rm -f PARSE/parseIt)
	make -C second-stage real-clean

########################################################################
#                                                                      #
# nbesttrain -- Preparing the N-best training data for the reranker    #
#                                                                      #
########################################################################

# To build the 20-fold n-best data in second-stage/train 
# for training the ranker, run
#
# make nbesttrain 
#
# or
# 
# make -j 2 nbesttrain
#
# on a multiprocessor machine

# TRAIN specifies the location of the trees to be divided into NFOLDS
# This is defined here to use sections 2-21 of the Penn WSJ treebank.
#
TRAIN=$(PENNWSJTREEBANK)/0[2-9]/*mrg $(PENNWSJTREEBANK)/1[0-9]/*mrg $(PENNWSJTREEBANK)/2[0-1]/*mrg

# NBESTDIR is the directory that holds the n-best parses for training
# the reranker.
#
NBESTDIR=second-stage/nbest/$(PARSERNICKNAME)$(NPARSES)

# NBESTFILES are all of the files in the n-best folds, plus dev and test sections
#
NBESTFILES= $(foreach fold,$(FOLDS),$(NBESTDIR)/fold$(fold).gz) $(foreach section,$(SECTIONS),$(NBESTDIR)/section$(section).gz)

.PHONY: nbesttrain
nbesttrain: $(NBESTFILES) PARSE TRAIN second-stage/programs/prepare-data/ptb

# This goal copies and gzips the output of the n-best parser
# into the appropriate directory for training the reranker.
#
# .PRECIOUS: $(NBESTDIR)/fold%.gz
.INTERMEDIATE: $(NBESTDIR)/fold%.gz
$(NBESTDIR)/fold%.gz: $(TMP)/fold%/$(NPARSES)best
	mkdir -p $(NBESTDIR)
	gzip -c $+ > $@

# The remaining goals in this section are for training and parsing
# with the n-best parser to produce the folds for training the
# reranker.

.INTERMEDIATE: $(TMP)/fold%/$(NPARSES)best
$(TMP)/fold%/$(NPARSES)best: $(TMP)/fold%/DATA $(TMP)/fold%/yield $(NBESTPARSER)
	$(NBESTPARSER) -l400 -K -N$(NPARSES) $(@D)/DATA/ $(@D)/yield > $@

.INTERMEDIATE: $(TMP)/fold%/DATA
$(TMP)/fold%/DATA: $(TMP)/fold%/train $(TMP)/fold%/dev $(NBESTTRAINER)
	mkdir -p $@
	LC_COLLATE=C; cp first-stage/DATA/EN/[a-z]* $@
	$(NBESTTRAINER) $@ $(@D)/train $(@D)/dev

.INTERMEDIATE: $(TMP)/fold%/train
$(TMP)/fold%/train: second-stage/programs/prepare-data/ptb
	mkdir -p $(@D)
	second-stage/programs/prepare-data/ptb -n $(NFOLDS) -x $(patsubst $(TMP)/fold%,%,$(@D)) -e $(TRAIN)  > $@

.INTERMEDIATE: $(TMP)/fold%/dev
$(TMP)/fold%/dev: second-stage/programs/prepare-data/ptb
	mkdir -p $(@D)
	second-stage/programs/prepare-data/ptb -n $(NFOLDS) -i $(patsubst $(TMP)/fold%,%,$(@D)) -e $(TRAIN)  > $@

# $(TMP)/fold%/DATA: $(TMP)/%/train $(TMP)/%/dev
# 	mkdir -p $@
# 	LC_COLLATE=C; cp first-stage/DATA/EN/[a-z]* $@
# 	first-stage/TRAIN/trainParser $@ $(@D)/train $(@D)/dev

.INTERMEDIATE: $(TMP)/fold%/yield
$(TMP)/fold%/yield: second-stage/programs/prepare-data/ptb
	mkdir -p $(@D)
	second-stage/programs/prepare-data/ptb -n $(NFOLDS) -i $(patsubst $(TMP)/fold%,%,$(@D)) -c $(TRAIN) > $@

# .PRECIOUS: $(NBESTDIR)/section%.gz
.INTERMEDIATE: $(NBESTDIR)/section%.gz
$(NBESTDIR)/section%.gz: $(TMP)/section%/$(NPARSES)best
	mkdir -p $(NBESTDIR)
	gzip -c $+ > $@

.INTERMEDIATE: $(TMP)/section%/$(NPARSES)best
$(TMP)/section%/$(NPARSES)best: $(TMP)/section%/yield $(NBESTPARSER)
	$(NBESTPARSER) -l400 -K -N$(NPARSES) first-stage/DATA/EN/ $(@D)/yield > $@

.INTERMEDIATE: $(TMP)/section%/yield
$(TMP)/section%/yield: second-stage/programs/prepare-data/ptb
	mkdir -p $(@D)
	second-stage/programs/prepare-data/ptb -c $(PENNWSJTREEBANK)/$(patsubst $(TMP)/section%,%,$(@D))/wsj*.mrg  > $@

########################################################################
#                                                                      #
# nbest oracle evaluation                                              #
#                                                                      #
########################################################################

.PHONY: nbest-oracle
nbest-oracle: second-stage/programs/features/oracle-score second-stage/programs/prepare-data/ptb $(NBESTFILES)
	second-stage/programs/features/oracle-score "zcat $(NBESTDIR)/fold[0-1][0-9].gz" "second-stage/programs/prepare-data/ptb -g $(TRAIN)"
	second-stage/programs/features/oracle-score "zcat $(NBESTDIR)/section22.gz" "second-stage/programs/prepare-data/ptb -g $(PENNWSJTREEBANK)/22/wsj*.mrg"
	second-stage/programs/features/oracle-score "zcat $(NBESTDIR)/section24.gz" "second-stage/programs/prepare-data/ptb -g $(PENNWSJTREEBANK)/24/wsj*.mrg"

.PHONY: nbest-oracle-detailed
nbest-oracle-detailed: second-stage/programs/eval-beam/main second-stage/programs/prepare-data/ptb $(NBESTFILES)
	second-stage/programs/eval-beam/main "zcat $(NBESTDIR)/fold[0-1][0-9].gz" "second-stage/programs/prepare-data/ptb -g $(TRAIN)"
	second-stage/programs/eval-beam/main "zcat $(NBESTDIR)/section22.gz" "second-stage/programs/prepare-data/ptb -g $(PENNWSJTREEBANK)/22/wsj*.mrg"
	second-stage/programs/eval-beam/main "zcat $(NBESTDIR)/section24.gz" "second-stage/programs/prepare-data/ptb -g $(PENNWSJTREEBANK)/24/wsj*.mrg"

########################################################################
#                                                                      #
# extract-features extracts feature counts for training reranker       #
#                                                                      #
########################################################################

# FEATBASEDIR is the directory in which the feature counts will be saved,
# minus the $(VERSION) flag.
#
FEATBASEDIR=second-stage/features/$(PARSERNICKNAME)$(NPARSES)$(FEATURESNICKNAME)

# FEATDIR is the directory in which the feature counts will be saved.
#
FEATDIR=$(FEATBASEDIR)$(VERSION)

# MODELBASEDIR is the directory in which the features and feature
# weights are saved, minus the version.
#
MODELBASEDIR=second-stage/models/$(PARSERNICKNAME)$(NPARSES)$(FEATURESNICKNAME)

# MODELDIR is the directory in which the features and feature weights
# are saved.
#
MODELDIR=$(MODELBASEDIR)$(VERSION)

.PHONY: features
features: $(MODELDIR)/features.gz $(FEATDIR)/train.gz $(FEATDIR)/dev.gz $(FEATDIR)/test1.gz $(FEATDIR)/test2.gz

# This goal does feature extraction for reranker training for the
# nonfinal case (i.e., train is folds 0-17, dev is folds 18-19, test1
# is section 22 and test2 is section 24).
#
$(MODELBASEDIR)nonfinal/features.gz $(FEATBASEDIR)nonfinal/train.gz $(FEATBASEDIR)nonfinal/dev.gz $(FEATBASEDIR)nonfinal/test1.gz $(FEATBASEDIR)nonfinal/test2.gz: second-stage/programs/prepare-data/ptb $(FEATUREEXTRACTOR) $(NBESTFILES)
	mkdir -p $(FEATBASEDIR)nonfinal
	mkdir -p $(MODELBASEDIR)nonfinal
	$(FEATUREEXTRACTOR) $(FEATUREEXTRACTORFLAGS) \
		"zcat $(NBESTDIR)/fold0[0-9].gz $(NBESTDIR)/fold1[0-7].gz" \
		"second-stage/programs/prepare-data/ptb -g -n 10 -x 9 $(TRAIN)" \
		$(FEATBASEDIR)nonfinal/train.gz \
		"zcat $(NBESTDIR)/fold1[8-9].gz" \
		"second-stage/programs/prepare-data/ptb -g -n 10 -i 9 $(TRAIN)" \
		$(FEATBASEDIR)nonfinal/dev.gz \
		"zcat $(NBESTDIR)/section22.gz" \
		"second-stage/programs/prepare-data/ptb -g $(PENNWSJTREEBANK)/22/*mrg" \
		$(FEATBASEDIR)nonfinal/test1.gz \
		"zcat $(NBESTDIR)/section24.gz" \
		"second-stage/programs/prepare-data/ptb -g $(PENNWSJTREEBANK)/24/*mrg" \
		$(FEATBASEDIR)nonfinal/test2.gz \
		| gzip > $(MODELBASEDIR)nonfinal/features.gz

# This goal does feature extraction for reranker training for the
# final case (i.e., train is folds 0-19, dev is section 24, test1
# is section 22 and test2 is section 23).
#
$(MODELBASEDIR)final/features.gz $(FEATBASEDIR)final/train.gz $(FEATBASEDIR)final/dev.gz $(FEATBASEDIR)final/test1.gz $(FEATBASEDIR)final/test2.gz: second-stage/programs/prepare-data/ptb $(FEATUREEXTRACTOR) $(NBESTFILES)
	mkdir -p $(FEATBASEDIR)final
	mkdir -p $(MODELBASEDIR)final
	$(FEATUREEXTRACTOR) $(FEATUREEXTRACTORFLAGS) \
		"zcat $(NBESTDIR)/fold*.gz" \
		"second-stage/programs/prepare-data/ptb -g $(TRAIN)" \
		$(FEATBASEDIR)final/train.gz \
		"zcat $(NBESTDIR)/section22.gz" \
		"second-stage/programs/prepare-data/ptb -g $(PENNWSJTREEBANK)/22/*mrg" \
		$(FEATBASEDIR)final/test1.gz \
		"zcat $(NBESTDIR)/section23.gz" \
		"second-stage/programs/prepare-data/ptb -g $(PENNWSJTREEBANK)/23/*mrg" \
		$(FEATBASEDIR)final/test2.gz \
		"zcat $(NBESTDIR)/section24.gz" \
		"second-stage/programs/prepare-data/ptb -g $(PENNWSJTREEBANK)/24/*mrg" \
		$(FEATBASEDIR)final/dev.gz \
		| gzip > $(MODELBASEDIR)final/features.gz


########################################################################
#                                                                      #
# train-reranker estimates the reranker feature weights                #
#                                                                      #
########################################################################

WEIGHTSFILE=$(MODELDIR)/$(ESTIMATORNICKNAME)-weights
WEIGHTSFILEGZ=$(WEIGHTSFILE).gz

.PHONY: train-reranker
train-reranker: $(WEIGHTSFILEGZ)

# This goal estimates the reranker feature weights (i.e., trains the
# reranker).  This is not hard to parallelize, but I haven't actually
# done that yet.
#
# $(WEIGHTSFILEGZ): $(ESTIMATOR)
$(WEIGHTSFILEGZ): $(ESTIMATOR) $(MODELDIR)/features.gz $(FEATDIR)/train.gz $(FEATDIR)/dev.gz $(FEATDIR)/test1.gz
	zcat $(FEATDIR)/train.gz | $(ESTIMATOR) $(ESTIMATORFLAGS) -e $(FEATDIR)/dev.gz -f $(MODELDIR)/features.gz -o $(WEIGHTSFILE) -x $(FEATDIR)/test1.gz
	rm -f $(WEIGHTSFILEGZ)
	gzip $(WEIGHTSFILE)

########################################################################
#                                                                      #
# eval-reranker evaluates the reranker on the two test data sets       #
#                                                                      #
########################################################################

EVALDIR=second-stage/eval/$(PARSERNICKNAME)$(NPARSES)$(FEATURESNICKNAME)$(VERSION)-$(ESTIMATORNICKNAME)

.PHONY: eval-reranker
eval-reranker: $(EVALDIR)/weights-eval # $(EVALDIR)/dev-parsediffs.gz

$(EVALDIR)/weights-eval: $(WEIGHTSFILEGZ) $(MODELDIR)/features.gz $(FEATDIR)/dev.gz $(FEATDIR)/test1.gz $(FEATDIR)/test2.gz second-stage/programs/eval-weights/eval-weights
	mkdir -p $(EVALDIR)
	zcat $(WEIGHTSFILEGZ) | second-stage/programs/eval-weights/eval-weights $(EVALWEIGHTSARGS) $(MODELDIR)/features.gz $(FEATDIR)/dev.gz > $(EVALDIR)/weights-eval
	zcat $(WEIGHTSFILEGZ) | second-stage/programs/eval-weights/eval-weights $(EVALWEIGHTSARGS) $(MODELDIR)/features.gz $(FEATDIR)/test1.gz >> $(EVALDIR)/weights-eval
	zcat $(WEIGHTSFILEGZ) | second-stage/programs/eval-weights/eval-weights $(EVALWEIGHTSARGS) $(MODELDIR)/features.gz $(FEATDIR)/test2.gz >> $(EVALDIR)/weights-eval

$(EVALDIR)/dev-parsediffs.gz: $(WEIGHTSFILEGZ) $(FEATDIR)/test1.gz $(NBESTDIR)/section24.gz second-stage/programs/eval-weights/best-indices second-stage/programs/eval-weights/best-parses second-stage/programs/eval-weights/pretty-print
	zcat $(WEIGHTSFILEGZ) \
	 | second-stage/programs/eval-weights/best-indices $(FEATDIR)/test1.gz \
	 | second-stage/programs/eval-weights/best-parses $(NBESTDIR)/section24.gz \
	 | second-stage/programs/eval-weights/pretty-print -d \
	 | gzip > $(EVALDIR)/dev-parsediffs.gz
Tip: Filter by directory path e.g. /media app.js to search for public/media/app.js.
Tip: Use camelCasing e.g. ProjME to search for ProjectModifiedEvent.java.
Tip: Filter by extension type e.g. /repo .js to search for all .js files in the /repo directory.
Tip: Separate your search with spaces e.g. /ssh pom.xml to search for src/ssh/pom.xml.
Tip: Use ↑ and ↓ arrow keys to navigate and return to view the file.
Tip: You can also navigate files with Ctrl+j (next) and Ctrl+k (previous) and view the file with Ctrl+o.
Tip: You can also navigate files with Alt+j (next) and Alt+k (previous) and view the file with Alt+o.