Sync to changes in PRs on which this one depends

projects/biaffine_parser/configs/base-config-transition.cfg

@@ -0,0 +1,173 @@
+[paths]
+train = null
+dev = null
+
+[system]
+gpu_allocator = "pytorch"
+seed = 0
+
+[nlp]
+lang = null
+pipeline = ["transformer","tagger","morphologizer","senter","parser"]
+disabled = ["senter"]
+before_creation = null
+after_creation = null
+after_pipeline_creation = null
+batch_size = 64
+tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
+
+[components]
+
+[components.parser]
+factory = "parser"
+learn_tokens = false
+min_action_freq = 30
+moves = null
+scorer = {"@scorers":"spacy.parser_scorer.v1"}
+update_with_oracle_cut_size = 100
+
+[components.parser.model]
+@architectures = "spacy.TransitionBasedParser.v2"
+state_type = "parser"
+extra_state_tokens = false
+hidden_width = 64
+maxout_pieces = 2
+use_upper = false
+nO = null
+
+[components.parser.model.tok2vec]
+@architectures = "spacy-transformers.TransformerListener.v1"
+grad_factor = 1.0
+upstream = "transformer"
+pooling = {"@layers":"reduce_mean.v1"}
+
+[components.transformer]
+factory = "transformer"
+max_batch_items = 4096
+set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"}
+
+[components.transformer.model]
+@architectures = "spacy-transformers.TransformerModel.v3"
+name = null
+tokenizer_config = {"use_fast": true}
+mixed_precision = true
+
+[components.transformer.model.get_spans]
+@span_getters = "spacy-transformers.strided_spans.v1"
+window = 128
+stride = 96
+
+[components.morphologizer]
+factory = "morphologizer"
+
+[components.morphologizer.model]
+@architectures = "spacy.Tagger.v1"
+nO = null
+
+[components.morphologizer.model.tok2vec]
+@architectures = "spacy-transformers.TransformerListener.v1"
+grad_factor = 1.0
+upstream = "transformer"
+pooling = {"@layers":"reduce_mean.v1"}
+
+[components.senter]
+factory = "senter"
+store_activations = true
+
+[components.senter.model]
+@architectures = "spacy.Tagger.v1"
+nO = null
+
+[components.senter.model.tok2vec]
+@architectures = "spacy-transformers.TransformerListener.v1"
+grad_factor = 1.0
+upstream = "transformer"
+pooling = {"@layers":"reduce_mean.v1"}
+
+[components.tagger]
+factory = "tagger"
+
+[components.tagger.model]
+@architectures = "spacy.Tagger.v1"
+nO = null
+
+[components.tagger.model.tok2vec]
+@architectures = "spacy-transformers.TransformerListener.v1"
+grad_factor = 1.0
+upstream = "transformer"
+pooling = {"@layers":"reduce_mean.v1"}
+
+[corpora]
+
+[corpora.train]
+@readers = "spacy.Corpus.v1"
+path = ${paths.train}
+max_length = 500
+gold_preproc = false
+limit = 0
+augmenter = null
+
+[corpora.dev]
+@readers = "spacy.Corpus.v1"
+max_length = 0
+path = ${paths.dev}
+gold_preproc = false
+limit = 0
+augmenter = null
+
+[training]
+train_corpus = "corpora.train"
+dev_corpus = "corpora.dev"
+seed = ${system:seed}
+gpu_allocator = ${system:gpu_allocator}
+dropout = 0.1
+accumulate_gradient = 3
+patience = 5000
+max_epochs = 0
+max_steps = 20000
+eval_frequency = 1000
+frozen_components = []
+before_to_disk = null
+annotating_components = []
+
+[training.batcher]
+@batchers = "spacy.batch_by_padded.v1"
+discard_oversize = true
+get_length = null
+size = 2000
+buffer = 256
+
+[training.logger]
+@loggers = "spacy.ConsoleLogger.v1"
+progress_bar = true
+
+[training.optimizer]
+@optimizers = "Adam.v1"
+beta1 = 0.9
+beta2 = 0.999
+L2_is_weight_decay = true
+L2 = 0.01
+grad_clip = 1.0
+use_averages = true
+eps = 0.00000001
+
+[training.optimizer.learn_rate]
+@schedules = "warmup_linear.v1"
+warmup_steps = 250
+total_steps = 20000
+initial_rate = 0.00005
+
+[training.score_weights]
+tag_acc = 0.2
+pos_acc = 0.2
+morph_acc = 0.2
+morph_per_feat = null
+dep_uas = 0.0
+dep_las = 0.2
+dep_las_per_type = null
+sents_p = null
+sents_r = null
+sents_f = 0.2
+
+[initialize]
+vectors = null

projects/biaffine_parser/configs/base-config.cfg

@@ -79,7 +79,7 @@ pooling = {"@layers":"reduce_mean.v1"}
 
 [components.senter]
 factory = "senter"
-store_activations = true
+save_activations = true
 
 [components.senter.model]
 @architectures = "spacy.Tagger.v1"

spacy_experimental/biaffine_parser/arc_predicter.pyx

@@ -319,7 +319,7 @@ def split_lazily(docs: List[Doc], *, ops: Ops, max_length: int, senter: Sentence
         activations = doc.activations.get(senter.name, None)
         if activations is None:
             raise ValueError("Greedy splitting requires senter with `store_activations` enabled.")
-        scores = activations['probs']
+        scores = activations['probabilities']
         split_recursive(scores[:,1], ops, max_length, lens)
 
     assert sum(lens) == sum([len(doc) for doc in docs])