Fix CharTie multi-threading
This commit is contained in:
@@ -3,12 +3,12 @@ use pyo3::prelude::*;
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use rayon::prelude::*;
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// Node in our character trie
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#[derive(Default)]
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#[derive(Clone, Default)]
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struct CharTrieNode {
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// Store character and node pairs, keep sorted for binary search
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children: Vec<(char, CharTrieNode)>,
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// Store token IDs that are valid at this point
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token_id: Option<Py<PyAny>>,
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token_id: Option<Arc<Py<PyAny>>>,
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}
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impl CharTrieNode {
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@@ -25,15 +25,14 @@ impl CharTrieNode {
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}
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// Add a token id to this node
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fn add_token(&mut self, token_id: Py<PyAny>) {
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fn add_token(&mut self, token_id: Arc<Py<PyAny>>) {
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self.token_id = Some(token_id);
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}
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fn find_invalid_tokens(
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&self,
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py: Python<'_>,
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xml_validator: &XmlSchemaValidator,
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) -> Vec<Py<PyAny>> {
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) -> Vec<Arc<Py<PyAny>>> {
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let res = self
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.children
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.iter()
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@@ -41,10 +40,10 @@ impl CharTrieNode {
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let mut node_validator = xml_validator.clone();
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if node_validator.append_char(*c).is_ok() {
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// If the node is valid, recursively check its children
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n.find_invalid_tokens(py, &node_validator)
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n.find_invalid_tokens(&node_validator)
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} else {
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// If the node is invalid, add it and its children to the list of invalid tokens
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n.all_tokens(py)
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n.all_tokens()
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}
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})
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.flatten()
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@@ -55,11 +54,8 @@ impl CharTrieNode {
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// Parallel version of find_invalid_tokens for the first level of recursion
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fn find_invalid_tokens_parallel(
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&self,
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_py: Python<'_>,
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xml_validator: &XmlSchemaValidator,
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) -> Vec<Py<PyAny>> {
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// We need to use the Python GIL to share PyAny objects across threads
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Python::with_gil(|_py| {
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) -> Vec<Arc<Py<PyAny>>> {
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// Convert children to a parallel iterator
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self.children
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.par_iter() // Use parallel iterator from rayon
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@@ -70,50 +66,30 @@ impl CharTrieNode {
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// Process this character
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if node_validator.append_char(*c).is_ok() {
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// For valid nodes, use the regular (non-parallel) method for deeper levels
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Python::with_gil(|py| {
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n.find_invalid_tokens(py, &node_validator)
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})
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n.find_invalid_tokens(&node_validator)
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} else {
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// For invalid nodes, get all tokens
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Python::with_gil(|py| {
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n.all_tokens(py)
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})
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n.all_tokens()
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}
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})
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.flatten()
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.collect()
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})
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}
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fn all_tokens(&self, py: Python<'_>) -> Vec<Py<PyAny>> {
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fn all_tokens(&self) -> Vec<Arc<Py<PyAny>>> {
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let mut tokens = Vec::new();
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if let Some(token_id) = &self.token_id {
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tokens.push(token_id.clone_ref(py));
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tokens.push(token_id.clone());
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}
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for (_, child) in &self.children {
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tokens.extend(child.all_tokens(py));
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tokens.extend(child.all_tokens());
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}
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tokens
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}
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fn clone_ref(&self, py: Python<'_>) -> Self {
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Self {
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children: self
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.children
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.iter()
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.map(|(ch, node)| (*ch, node.clone_ref(py)))
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.collect(),
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token_id: self
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.token_id
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.iter()
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.map(|token_id| token_id.clone_ref(py))
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.nth(0),
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}
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}
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}
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// The main trie structure
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#[derive(Default)]
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#[derive(Clone, Default)]
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pub struct CharTrie {
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root: CharTrieNode,
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}
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@@ -129,22 +105,15 @@ impl CharTrie {
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}
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// Mark this node as representing token_id
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current.add_token(token_id);
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current.add_token(Arc::new(token_id));
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}
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// Find all tokens that could be invalid given the current XML state
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pub fn find_invalid_tokens(
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&self,
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py: Python<'_>,
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xml_validator: &XmlSchemaValidator,
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) -> Vec<Py<PyAny>> {
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) -> Vec<Arc<Py<PyAny>>> {
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// Use the parallel version starting at the root
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self.root.find_invalid_tokens_parallel(py, xml_validator)
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}
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pub fn clone_ref(&self, py: Python<'_>) -> Self {
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Self {
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root: self.root.clone_ref(py),
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}
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self.root.find_invalid_tokens_parallel(xml_validator)
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}
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}
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@@ -4,6 +4,7 @@ use pyo3::types::PyDict;
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/// A minimal LogitsProcessor that enforces valid XML according to a schema.
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#[pyclass]
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#[derive(Clone)]
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pub struct XmlLogitsProcessorCore {
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xml_schema_validator: XmlSchemaValidator,
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trie: char_trie::CharTrie,
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@@ -41,7 +42,10 @@ impl XmlLogitsProcessorCore {
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fn get_invalid_tokens(&mut self, py: Python<'_>) -> PyResult<Vec<PyObject>> {
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Ok(self
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.trie
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.find_invalid_tokens(py, &self.xml_schema_validator))
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.find_invalid_tokens(&self.xml_schema_validator)
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.iter()
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.map(|token_id| token_id.clone_ref(py))
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.collect())
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}
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/// Check if the validator has reached the end of the XML
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@@ -50,11 +54,8 @@ impl XmlLogitsProcessorCore {
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}
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/// Create a copy of the processor
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fn copy(&self, py: Python<'_>) -> PyResult<Self> {
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Ok(Self {
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xml_schema_validator: self.xml_schema_validator.clone(),
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trie: self.trie.clone_ref(py),
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})
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fn copy(&self) -> PyResult<Self> {
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Ok(self.clone())
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}
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/// Get a list of all element names in the schema
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@@ -258,7 +259,7 @@ processed_scores = processor(input_ids, scores)
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let processor = create_test_processor(py).unwrap();
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// Make a copy
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let copy = processor.copy(py).unwrap();
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let copy = processor.copy().unwrap();
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// Original and copy should behave the same
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assert_eq!(
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@@ -268,7 +269,7 @@ processed_scores = processor(input_ids, scores)
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);
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// Modify copy, original should be unchanged
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let mut copy = processor.copy(py).unwrap();
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let mut copy = processor.copy().unwrap();
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assert!(copy.append("<reasoning>"), "Copy should accept XML");
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assert!(!processor.eof().unwrap(), "Original should be unchanged");
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assert!(!copy.eof().unwrap(), "Copy should be modified");
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@@ -345,7 +346,7 @@ processed_scores = processor(input_ids, scores)
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// Now try to append each character of "<reasoning>" one by one
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let chars = vec!['<', 'r', 'e', 'a', 's', 'o', 'n', 'i', 'n', 'g', '>'];
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let mut full_text = String::new();
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let processor = processor.copy(py).unwrap();
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let processor = processor.copy().unwrap();
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for c in chars {
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full_text.push(c);
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@@ -373,7 +374,7 @@ processed_scores = processor(input_ids, scores)
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if element_names.contains(&"reasoning".to_string()) {
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// Test appending "<reasoning>" to a fresh processor
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let mut processor = processor.copy(py).unwrap();
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let mut processor = processor.copy().unwrap();
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let result = processor.append("<reasoning>");
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println!("Appending '<reasoning>' to fresh processor: {}", result);
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@@ -18,67 +18,67 @@ xml_schema_only_root_node = """<?xml version="1.0" encoding="UTF-8"?>
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</xs:element>
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</xs:schema>"""
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#def test_logits_processor_init_copy():
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# """Test the initialization of the LogitsProcessor"""
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#
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# tokenizer = AutoTokenizer.from_pretrained(model_path, token=api_token)
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# logits_processor = XmlLogitsProcessor(tokenizer, xml_schema_only_root_node)
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# assert logits_processor.core is not None
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#
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# logits_processor_copy = logits_processor.copy()
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# assert logits_processor_copy.core is not None
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#
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#def test_xml_schema_parsing():
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# """Test basic XML schema parsing with different element types"""
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#
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# tokenizer = AutoTokenizer.from_pretrained(model_path, token=api_token)
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# logits_processor = XmlLogitsProcessor(tokenizer, xml_schema_only_root_node)
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# assert logits_processor.core is not None
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#
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# element_names = logits_processor.core.get_element_names()
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# assert len(element_names) > 0
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# assert "root" in element_names
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#
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#def test_basic_xml_validation():
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# """Test basic validation of XML fragments against the schema"""
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#
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# tokenizer = AutoTokenizer.from_pretrained(model_path, token=api_token)
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# processor = XmlLogitsProcessor(tokenizer, xml_schema_actions)
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#
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# # Test appending valid XML fragments
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# assert processor.core.copy().append("<reasoning>")
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# assert processor.core.copy().append("<reasoning>Test content</reasoning>")
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#
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# # Test appending invalid XML fragments
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# assert not processor.core.copy().append("<invalid>")
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# assert not processor.core.copy().append("<reasoning></invalid>")
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#
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#def test_token_masking():
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# """Test that invalid tokens are properly masked"""
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#
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# tokenizer = AutoTokenizer.from_pretrained(model_path, token=api_token)
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# processor = XmlLogitsProcessor(tokenizer, xml_schema_actions)
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#
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# # Process empty input to set prompt length
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# input_ids = torch.tensor([tokenizer.encode("")])
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# scores = torch.ones((1, len(tokenizer))) # All tokens have equal probability
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# processed_scores = processor(input_ids, scores)
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#
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# # Process valid continuation
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# input_ids = torch.tensor([tokenizer.encode("<reasoning>")])
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# scores = torch.ones((1, len(tokenizer))) # All tokens have equal probability
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# processed_scores = processor(input_ids, scores)
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#
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# # Verify that valid continuations still have positive scores
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# space_token = tokenizer.encode(" ", add_special_tokens=False)[0]
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# assert processed_scores[0, space_token] > -float('inf')
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#
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# # Verify that invalid continuations are masked
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# input_ids = torch.tensor([tokenizer.encode("</invalid>")])
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# scores = torch.ones((1, len(tokenizer))) # All tokens have equal probability
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# processed_scores = processor(input_ids, scores)
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# assert processed_scores[0, tokenizer.eos_token_id] == 1
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# assert processed_scores[0, space_token] == -float('inf')
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def test_logits_processor_init_copy():
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"""Test the initialization of the LogitsProcessor"""
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tokenizer = AutoTokenizer.from_pretrained(model_path, token=api_token)
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logits_processor = XmlLogitsProcessor(tokenizer, xml_schema_only_root_node)
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assert logits_processor.core is not None
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logits_processor_copy = logits_processor.copy()
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assert logits_processor_copy.core is not None
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def test_xml_schema_parsing():
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"""Test basic XML schema parsing with different element types"""
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tokenizer = AutoTokenizer.from_pretrained(model_path, token=api_token)
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logits_processor = XmlLogitsProcessor(tokenizer, xml_schema_only_root_node)
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assert logits_processor.core is not None
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element_names = logits_processor.core.get_element_names()
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assert len(element_names) > 0
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assert "root" in element_names
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def test_basic_xml_validation():
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"""Test basic validation of XML fragments against the schema"""
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tokenizer = AutoTokenizer.from_pretrained(model_path, token=api_token)
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processor = XmlLogitsProcessor(tokenizer, xml_schema_actions)
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# Test appending valid XML fragments
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assert processor.core.copy().append("<reasoning>")
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assert processor.core.copy().append("<reasoning>Test content</reasoning>")
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# Test appending invalid XML fragments
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assert not processor.core.copy().append("<invalid>")
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assert not processor.core.copy().append("<reasoning></invalid>")
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def test_token_masking():
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"""Test that invalid tokens are properly masked"""
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tokenizer = AutoTokenizer.from_pretrained(model_path, token=api_token)
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processor = XmlLogitsProcessor(tokenizer, xml_schema_actions)
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# Process empty input to set prompt length
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input_ids = torch.tensor([tokenizer.encode("")])
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scores = torch.ones((1, len(tokenizer))) # All tokens have equal probability
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processed_scores = processor(input_ids, scores)
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# Process valid continuation
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input_ids = torch.tensor([tokenizer.encode("<reasoning>")])
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scores = torch.ones((1, len(tokenizer))) # All tokens have equal probability
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processed_scores = processor(input_ids, scores)
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# Verify that valid continuations still have positive scores
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space_token = tokenizer.encode(" ", add_special_tokens=False)[0]
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assert processed_scores[0, space_token] > -float('inf')
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# Verify that invalid continuations are masked
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input_ids = torch.tensor([tokenizer.encode("</invalid>")])
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scores = torch.ones((1, len(tokenizer))) # All tokens have equal probability
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processed_scores = processor(input_ids, scores)
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assert processed_scores[0, tokenizer.eos_token_id] == 1
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assert processed_scores[0, space_token] == -float('inf')
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def test_delete():
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"""Test that invalid tokens are properly masked"""
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@@ -100,8 +100,8 @@ def test_delete():
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if __name__ == "__main__":
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# Run individual tests for debugging
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#test_logits_processor_init_copy()
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#test_xml_schema_parsing()
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#test_basic_xml_validation()
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#test_token_masking()
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test_logits_processor_init_copy()
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test_xml_schema_parsing()
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test_basic_xml_validation()
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test_token_masking()
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test_delete()
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