ci: update version string in docs

.github/workflows/rust.yml

@@ -781,8 +781,6 @@ jobs:
         run: python -m venv .env --clear; source .env/bin/activate; pip install -r requirements.txt; python -m ensurepip --upgrade
       - name: Build python ezkl
         run: source .env/bin/activate; unset CONDA_PREFIX; maturin develop --features python-bindings --profile=test-runs
-      - name: Cat and Dog notebook
-        run: source .env/bin/activate; cargo nextest run py_tests::tests::cat_and_dog_notebook_
       - name: All notebooks
         run: source .env/bin/activate; cargo nextest run py_tests::tests::run_notebook_ --test-threads 1
       - name: Voice tutorial

docs/python/src/conf.py

@@ -1,7 +1,7 @@
 import ezkl
 
 project = 'ezkl'
-release = '20.0.3'
+release = '20.0.1'
 version = release
 
 

examples/notebooks/cat_and_dog_data.sh

@@ -1,13 +0,0 @@
-# download tess data
-# check if first argument has been set 
-if [ ! -z "$1" ]; then
-    DATA_DIR=$1
-else
-    DATA_DIR=data
-fi
-
-echo "Downloading data to $DATA_DIR"
-
-if [ ! -d "$DATA_DIR/CATDOG" ]; then
-    kaggle datasets download tongpython/cat-and-dog -p $DATA_DIR/CATDOG --unzip
-fi

src/bindings/python.rs

@@ -597,7 +597,7 @@ fn poseidon_hash(message: Vec<PyFelt>) -> PyResult<Vec<PyFelt>> {
 /// Arguments
 /// -------
 /// message: list[str]
-///     List of field elements represented as strings
+///     List of field elements represnted as strings
 ///
 /// vk_path: str
 ///     Path to the verification key
@@ -656,7 +656,7 @@ fn kzg_commit(
 /// Arguments
 /// -------
 /// message: list[str]
-///     List of field elements represented as strings
+///     List of field elements represnted as strings
 ///
 /// vk_path: str
 ///     Path to the verification key
@@ -1950,7 +1950,7 @@ fn deploy_da_evm(
 ///     does the verifier use data attestation ?
 ///
 /// addr_vk: str
-///     The address of the separate VK contract (if the verifier key is rendered as a separate contract)
+///     The addess of the separate VK contract (if the verifier key is rendered as a separate contract)
 /// Returns
 /// -------
 /// bool

src/circuit/ops/layouts.rs

@@ -349,7 +349,7 @@ pub fn sqrt<F: PrimeField + TensorType + PartialOrd + std::hash::Hash>(
         .into()
     };
     claimed_output.reshape(input_dims)?;
-    // force the output to be positive or zero, also implicitly checks that the output is in range
+    // force the output to be positive or zero, also implicitly checks that the ouput is in range
     let claimed_output = abs(config, region, &[claimed_output.clone()])?;
     // rescaled input
     let rescaled_input = pairwise(config, region, &[input.clone(), unit_scale], BaseOp::Mult)?;
@@ -1841,7 +1841,7 @@ pub(crate) fn get_missing_set_elements<
 
         // get the difference between the two vectors
         for eval in input_evals.iter() {
-            // delete first occurrence of that value
+            // delete first occurence of that value
             if let Some(pos) = fullset_evals.iter().position(|x| x == eval) {
                 fullset_evals.remove(pos);
             }
@@ -1869,7 +1869,7 @@ pub(crate) fn get_missing_set_elements<
     region.increment(claimed_output.len());
 
     // input and claimed output should be the shuffles of fullset
-    // concatenate input and claimed output
+    // concatentate input and claimed output
     let input_and_claimed_output = input.concat(claimed_output.clone())?;
 
     // assert that this is a permutation/shuffle
@@ -3396,7 +3396,7 @@ pub fn max_pool<F: PrimeField + TensorType + PartialOrd + std::hash::Hash>(
 /// Performs a deconvolution on the given input tensor.
 /// # Examples
 /// ```
-// // expected outputs are taken from pytorch torch.nn.functional.conv_transpose2d
+// // expected ouputs are taken from pytorch torch.nn.functional.conv_transpose2d
 ///
 /// use ezkl::tensor::Tensor;
 /// use ezkl::fieldutils::IntegerRep;
@@ -3624,7 +3624,7 @@ pub fn deconv<
 
 /// Applies convolution over a ND tensor of shape C x H x D1...DN (and adds a bias).
 /// ```
-/// // expected outputs are taken from pytorch torch.nn.functional.conv2d
+/// // expected ouputs are taken from pytorch torch.nn.functional.conv2d
 ///
 /// use ezkl::tensor::Tensor;
 /// use ezkl::fieldutils::IntegerRep;
@@ -3908,7 +3908,7 @@ pub(crate) fn rescale<F: PrimeField + TensorType + PartialOrd + std::hash::Hash>
     Ok(rescaled_inputs)
 }
 
-/// Dummy (no constraints) reshape layout
+/// Dummy (no contraints) reshape layout
 pub(crate) fn reshape<F: PrimeField + TensorType + PartialOrd + std::hash::Hash>(
     values: &[ValTensor<F>; 1],
     new_dims: &[usize],
@@ -3918,7 +3918,7 @@ pub(crate) fn reshape<F: PrimeField + TensorType + PartialOrd + std::hash::Hash>
     Ok(t)
 }
 
-/// Dummy (no constraints) move_axis layout
+/// Dummy (no contraints) move_axis layout
 pub(crate) fn move_axis<F: PrimeField + TensorType + PartialOrd + std::hash::Hash>(
     values: &[ValTensor<F>; 1],
     source: usize,

tests/py_integration_tests.rs

@@ -49,23 +49,6 @@ mod py_tests {
         std::env::set_var("VOICE_DATA_DIR", format!("{}", voice_data_dir));
     }
 
-    fn download_catdog_data() {
-        let cat_and_dog_data_dir = shellexpand::tilde("~/data/catdog_data");
-
-        DOWNLOAD_VOICE_DATA.call_once(|| {
-            let status = Command::new("bash")
-                .args([
-                    "examples/notebooks/cat_and_dog_data.sh",
-                    &cat_and_dog_data_dir,
-                ])
-                .status()
-                .expect("failed to execute process");
-            assert!(status.success());
-        });
-        // set VOICE_DATA_DIR environment variable
-        std::env::set_var("CATDOG_DATA_DIR", format!("{}", cat_and_dog_data_dir));
-    }
-
     fn setup_py_env() {
         ENV_SETUP.call_once(|| {
             // supposes that you have a virtualenv called .env and have run the following
@@ -242,20 +225,6 @@ mod py_tests {
                 anvil_child.kill().unwrap();
             }
 
-
-            #[test]
-            fn cat_and_dog_notebook_() {
-                crate::py_tests::init_binary();
-                let mut anvil_child = crate::py_tests::start_anvil(false);
-                crate::py_tests::download_catdog_data();
-                let test_dir: TempDir = TempDir::new("cat_and_dog").unwrap();
-                let path = test_dir.path().to_str().unwrap();
-                crate::py_tests::mv_test_(path, "cat_and_dog.ipynb");
-                run_notebook(path, "cat_and_dog.ipynb");
-                test_dir.close().unwrap();
-                anvil_child.kill().unwrap();
-            }
-
             #[test]
             fn reusable_verifier_notebook_() {
                 crate::py_tests::init_binary();

tests/wasm.rs

@@ -337,7 +337,7 @@ mod wasm32 {
         // Run compiled circuit validation on onnx network (should fail)
         let circuit = compiledCircuitValidation(wasm_bindgen::Clamped(NETWORK.to_vec()));
         assert!(circuit.is_err());
-        // Run compiled circuit validation on compiled network (should pass)
+        // Run compiled circuit validation on comiled network (should pass)
         let circuit = compiledCircuitValidation(wasm_bindgen::Clamped(NETWORK_COMPILED.to_vec()));
         assert!(circuit.is_ok());
         // Run input validation on witness (should fail)