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https://github.com/karpathy/nanochat.git
synced 2025-12-06 04:12:13 +00:00
Add explicit UTF-8 encoding on open
This commit is contained in:
commit
df25293087
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@ -37,7 +37,7 @@ from concurrent.futures import ThreadPoolExecutor, as_completed
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from nanochat.common import get_base_dir
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from nanochat.common import get_base_dir
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api_key = open("openroutertoken.txt").read().strip()
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api_key = open("openroutertoken.txt", "r", encoding="utf-8").read().strip()
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url = "https://openrouter.ai/api/v1/chat/completions"
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url = "https://openrouter.ai/api/v1/chat/completions"
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headers = {
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headers = {
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@ -45,7 +45,7 @@ headers = {
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"Content-Type": "application/json"
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"Content-Type": "application/json"
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}
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}
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readme = open("README.md").read().strip()
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readme = open("README.md", "r", encoding="utf-8").read().strip()
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prompt = r"""
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prompt = r"""
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I want to generate synthetic data for an LLM to teach it about its identity. Here is the identity I want:
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I want to generate synthetic data for an LLM to teach it about its identity. Here is the identity I want:
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@ -34,7 +34,7 @@ def save_checkpoint(checkpoint_dir, step, model_data, optimizer_data, meta_data)
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log0(f"Saved optimizer file to: {optimizer_path}")
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log0(f"Saved optimizer file to: {optimizer_path}")
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# Save the metadata dict as json
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# Save the metadata dict as json
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meta_path = os.path.join(checkpoint_dir, f"meta_{step:06d}.json")
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meta_path = os.path.join(checkpoint_dir, f"meta_{step:06d}.json")
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with open(meta_path, "w") as f:
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with open(meta_path, "w", encoding="utf-8") as f:
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json.dump(meta_data, f, indent=2)
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json.dump(meta_data, f, indent=2)
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log0(f"Saved metadata file to: {meta_path}")
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log0(f"Saved metadata file to: {meta_path}")
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@ -50,7 +50,7 @@ def load_checkpoint(checkpoint_dir, step, device, load_optimizer=False):
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optimizer_data = torch.load(optimizer_path, map_location=device)
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optimizer_data = torch.load(optimizer_path, map_location=device)
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# Load the metadata
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# Load the metadata
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meta_path = os.path.join(checkpoint_dir, f"meta_{step:06d}.json")
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meta_path = os.path.join(checkpoint_dir, f"meta_{step:06d}.json")
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with open(meta_path, "r") as f:
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with open(meta_path, "r", encoding="utf-8") as f:
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meta_data = json.load(f)
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meta_data = json.load(f)
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return model_data, optimizer_data, meta_data
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return model_data, optimizer_data, meta_data
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@ -70,7 +70,7 @@ def download_file_with_lock(url, filename, postprocess_fn=None):
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if os.path.exists(file_path):
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if os.path.exists(file_path):
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return file_path
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return file_path
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with open(lock_path, 'w') as lock_file:
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with open(lock_path, 'w', encoding='utf-8') as lock_file:
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# Only a single rank can acquire this lock
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# Only a single rank can acquire this lock
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# All other ranks block until it is released
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# All other ranks block until it is released
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@ -170,7 +170,7 @@ Generated: {timestamp}
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# count dependencies via uv.lock
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# count dependencies via uv.lock
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uv_lock_lines = 0
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uv_lock_lines = 0
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if os.path.exists('uv.lock'):
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if os.path.exists('uv.lock'):
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with open('uv.lock', 'r') as f:
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with open('uv.lock', 'r', encoding='utf-8') as f:
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uv_lock_lines = len(f.readlines())
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uv_lock_lines = len(f.readlines())
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header += f"""
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header += f"""
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@ -241,7 +241,7 @@ class Report:
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slug = slugify(section)
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slug = slugify(section)
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file_name = f"{slug}.md"
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file_name = f"{slug}.md"
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file_path = os.path.join(self.report_dir, file_name)
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file_path = os.path.join(self.report_dir, file_name)
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with open(file_path, "w") as f:
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with open(file_path, "w", encoding="utf-8") as f:
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f.write(f"## {section}\n")
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f.write(f"## {section}\n")
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f.write(f"timestamp: {datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n")
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f.write(f"timestamp: {datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n")
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for item in data:
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for item in data:
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@ -272,11 +272,11 @@ class Report:
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final_metrics = {} # the most important final metrics we'll add as table at the end
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final_metrics = {} # the most important final metrics we'll add as table at the end
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start_time = None
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start_time = None
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end_time = None
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end_time = None
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with open(report_file, "w") as out_file:
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with open(report_file, "w", encoding="utf-8") as out_file:
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# write the header first
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# write the header first
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header_file = os.path.join(report_dir, "header.md")
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header_file = os.path.join(report_dir, "header.md")
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if os.path.exists(header_file):
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if os.path.exists(header_file):
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with open(header_file, "r") as f:
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with open(header_file, "r", encoding="utf-8") as f:
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header_content = f.read()
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header_content = f.read()
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out_file.write(header_content)
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out_file.write(header_content)
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start_time = extract_timestamp(header_content, "Run started:")
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start_time = extract_timestamp(header_content, "Run started:")
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@ -293,7 +293,7 @@ class Report:
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if not os.path.exists(section_file):
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if not os.path.exists(section_file):
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print(f"Warning: {section_file} does not exist, skipping")
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print(f"Warning: {section_file} does not exist, skipping")
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continue
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continue
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with open(section_file, "r") as in_file:
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with open(section_file, "r", encoding="utf-8") as in_file:
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section = in_file.read()
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section = in_file.read()
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# Extract timestamp from this section (the last section's timestamp will "stick" as end_time)
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# Extract timestamp from this section (the last section's timestamp will "stick" as end_time)
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if "rl" not in file_name:
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if "rl" not in file_name:
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@ -373,7 +373,7 @@ class Report:
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header_file = os.path.join(self.report_dir, "header.md")
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header_file = os.path.join(self.report_dir, "header.md")
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header = generate_header()
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header = generate_header()
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start_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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start_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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with open(header_file, "w") as f:
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with open(header_file, "w", encoding="utf-8") as f:
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f.write(header)
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f.write(header)
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f.write(f"Run started: {start_time}\n\n---\n\n")
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f.write(f"Run started: {start_time}\n\n---\n\n")
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print(f"Reset report and wrote header to {header_file}")
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print(f"Reset report and wrote header to {header_file}")
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@ -59,7 +59,7 @@ def evaluate_model(model, tokenizer, device, max_per_task=-1):
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config_path = os.path.join(eval_bundle_dir, "core.yaml")
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config_path = os.path.join(eval_bundle_dir, "core.yaml")
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data_base_path = os.path.join(eval_bundle_dir, "eval_data")
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data_base_path = os.path.join(eval_bundle_dir, "eval_data")
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eval_meta_data = os.path.join(eval_bundle_dir, "eval_meta_data.csv")
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eval_meta_data = os.path.join(eval_bundle_dir, "eval_meta_data.csv")
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with open(config_path, 'r') as f:
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with open(config_path, 'r', encoding='utf-8') as f:
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config = yaml.safe_load(f)
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config = yaml.safe_load(f)
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tasks = config['icl_tasks']
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tasks = config['icl_tasks']
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@ -193,7 +193,7 @@ def main():
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print0("="*80)
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print0("="*80)
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print0(f"Model: {model_name}")
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print0(f"Model: {model_name}")
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print0("="*80)
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print0("="*80)
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with open(output_csv_path, 'r') as f:
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with open(output_csv_path, 'r', encoding='utf-8') as f:
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print0(f.read())
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print0(f.read())
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# Log to report
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# Log to report
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@ -243,7 +243,7 @@ app.add_middleware(
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async def root():
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async def root():
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"""Serve the chat UI."""
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"""Serve the chat UI."""
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ui_html_path = os.path.join("nanochat", "ui.html")
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ui_html_path = os.path.join("nanochat", "ui.html")
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with open(ui_html_path, "r") as f:
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with open(ui_html_path, "r", encoding="utf-8") as f:
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html_content = f.read()
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html_content = f.read()
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# Replace the API_URL to use the same origin
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# Replace the API_URL to use the same origin
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html_content = html_content.replace(
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html_content = html_content.replace(
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@ -32,7 +32,7 @@ class CustomJSON(Task):
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print("-" * 80)
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print("-" * 80)
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else:
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else:
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with open(filepath, 'r') as f:
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with open(filepath, 'r', encoding='utf-8') as f:
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for line in f:
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for line in f:
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line = line.strip()
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line = line.strip()
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if not line: # skip empty lines
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if not line: # skip empty lines
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@ -119,7 +119,7 @@ class SpellingBee(Task):
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self.split = split
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self.split = split
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filename = WORD_LIST_URL.split("/")[-1]
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filename = WORD_LIST_URL.split("/")[-1]
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word_list_path = download_file_with_lock(WORD_LIST_URL, filename)
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word_list_path = download_file_with_lock(WORD_LIST_URL, filename)
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with open(word_list_path) as f:
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with open(word_list_path, 'r', encoding='utf-8') as f:
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words = [line.strip() for line in f]
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words = [line.strip() for line in f]
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self.words = words
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self.words = words
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@ -238,7 +238,7 @@ class SimpleSpelling(Task):
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self.split = split
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self.split = split
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filename = WORD_LIST_URL.split("/")[-1]
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filename = WORD_LIST_URL.split("/")[-1]
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word_list_path = download_file_with_lock(WORD_LIST_URL, filename)
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word_list_path = download_file_with_lock(WORD_LIST_URL, filename)
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with open(word_list_path) as f:
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with open(word_list_path, 'r', encoding='utf-8') as f:
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words = [line.strip() for line in f]
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words = [line.strip() for line in f]
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rng = random.Random(42)
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rng = random.Random(42)
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rng.shuffle(words) # use a different word order than the SpellingBee task
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rng.shuffle(words) # use a different word order than the SpellingBee task
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@ -455,13 +455,13 @@ def enwik8_path():
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@pytest.fixture(scope="module")
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@pytest.fixture(scope="module")
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def enwik8_small(enwik8_path):
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def enwik8_small(enwik8_path):
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"""Fixture providing 100KB of enwik8 for quick tests."""
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"""Fixture providing 100KB of enwik8 for quick tests."""
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with open(enwik8_path, "r") as f:
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with open(enwik8_path, "r", encoding="utf-8") as f:
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return f.read(100_000)
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return f.read(100_000)
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@pytest.fixture(scope="module")
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@pytest.fixture(scope="module")
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def enwik8_large(enwik8_path):
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def enwik8_large(enwik8_path):
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"""Fixture providing 10MB of enwik8 for performance tests."""
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"""Fixture providing 10MB of enwik8 for performance tests."""
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with open(enwik8_path, "r") as f:
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with open(enwik8_path, "r", encoding="utf-8") as f:
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return f.read(10**7)
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return f.read(10**7)
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def time_function(func, *args, **kwargs):
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def time_function(func, *args, **kwargs):
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