touhi99

from typing import Dict, Union
from huggingface_hub import get_safetensors_metadata
import argparse
import sys

# Example: 
# python get_gpu_memory.py Qwen/Qwen2.5-7B-Instruct

# Dictionary mapping dtype strings to their byte sizes
bytes_per_dtype: Dict[str, float] = {

touhi99

	def feature_template(self, state, sentence):
		feature_list = np.empty((0), int)
		stack = state.stack
		buffer = state.buffer
		ld = state.ld
		rd = state.rd
		form = sentence.form
		pos = sentence.pos
		lemma = sentence.lemma
		morph = sentence.morph

touhi99

def train(self, train_data):
		print("In trainer...")
		u= np.zeros(self.weights.shape, dtype=np.int32)
		q=0
		for epoch in range(0,1):
			correct=0
			print("epoch: ",epoch+1)
			i=0
			for data in train_data:
				q += 1

touhi99

	def generate_tree(self, node):
		#print(node)
		if isinstance(self.find(self.copy_table, node)[1], (list,)):
			item = self.find(self.copy_table, node)[1]
			item_x = self.find(self.copy_table, node)[2]
			item_y = self.find(self.copy_table, node)[3]
			self.copy_table.remove(node)

			if item_x[0]==0:
				x=self.copy_table_reversed[item_x[1]]

touhi99

#prod -> right-hand side one element
nt -> left-hand side non-terminal
count -> true, if prod is in left
  
  def create_prod_combinations(prod, nt, count):
	        numset = 1 << count
	        new_prods = []

	        for i in range(numset):
	            nth_nt = 0