Update documentation

Author: actions-user

releases/1.1.0/_downloads/0a692ff6fcb77ae473e504e58612751c/classification.py

@@ -57,6 +57,8 @@ def __init__(
             prepare_model=prepare_model,
         )
         self.bounds = Bounds([0.0, 0.0], [1.0, 1.0])
+        self.num_iterations_per_kernel: int | None = None
+        self.kernel_widths: List[float] | np.ndarray | None = None
 
     def generate_saliency_map(  # type: ignore
         self,

releases/1.1.0/_downloads/2b14cd654176fc7e07a5993fa4444c01/detection.py

@@ -57,6 +57,8 @@ def __init__(
         )
         self.deletion = False
         self.predictions = {}
+        self.num_iterations_per_kernel: int | None = None
+        self.divisors: List[float] | np.ndarray | None = None
 
     def generate_saliency_map(  # type: ignore
         self,

releases/1.1.0/_downloads/76561b11d66ce9f1c7ee1b3402ba9d23/rise.py

@@ -45,6 +45,8 @@ def __init__(
         super().__init__(
             model=model, postprocess_fn=postprocess_fn, preprocess_fn=preprocess_fn, device_name=device_name
         )
+        self.num_masks: int | None = None
+        self.num_cells: int | None = None
 
         if prepare_model:
             self.prepare_model()
@@ -84,13 +86,11 @@ def generate_saliency_map(
         """
         data_preprocessed = self.preprocess_fn(data)
 
-        num_masks, num_cells = self._preset_parameters(preset, num_masks, num_cells)
+        self.num_masks, self.num_cells = self._preset_parameters(preset, num_masks, num_cells)
 
         saliency_maps = self._run_synchronous_explanation(
             data_preprocessed,
             target_indices,
-            num_masks,
-            num_cells,
             prob,
             seed,
         )
@@ -134,8 +134,6 @@ def _run_synchronous_explanation(
         self,
         data_preprocessed: np.ndarray,
         target_classes: List[int] | None,
-        num_masks: int,
-        num_cells: int,
         prob: float,
         seed: int,
     ) -> np.ndarray:
@@ -152,8 +150,8 @@ def _run_synchronous_explanation(
         rand_generator = np.random.default_rng(seed=seed)
 
         saliency_maps = np.zeros((num_targets, input_size[0], input_size[1]))
-        for _ in tqdm(range(0, num_masks), desc="Explaining in synchronous mode"):
-            mask = self._generate_mask(input_size, num_cells, prob, rand_generator)
+        for _ in tqdm(range(0, self.num_masks), desc="Explaining in synchronous mode"):
+            mask = self._generate_mask(input_size, self.num_cells, prob, rand_generator)
             # Add channel dimensions for masks
             if is_bhwc_layout(data_preprocessed):
                 masked = np.expand_dims(mask, 2) * data_preprocessed

releases/1.1.0/_modules/openvino_xai/methods/black_box/aise/classification.html

@@ -456,6 +456,8 @@ <h1>Source code for openvino_xai.methods.black_box.aise.classification</h1><div
             <span class="n">prepare_model</span><span class="o">=</span><span class="n">prepare_model</span><span class="p">,</span>
         <span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">bounds</span> <span class="o">=</span> <span class="n">Bounds</span><span class="p">([</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">],</span> <span class="p">[</span><span class="mf">1.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">])</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">num_iterations_per_kernel</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">kernel_widths</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">|</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
 
 <div class="viewcode-block" id="AISEClassification.generate_saliency_map">
 <a class="viewcode-back" href="../../../../../api-manual.html#openvino_xai.methods.AISEClassification.generate_saliency_map">[docs]</a>

releases/1.1.0/_modules/openvino_xai/methods/black_box/aise/detection.html

@@ -456,6 +456,8 @@ <h1>Source code for openvino_xai.methods.black_box.aise.detection</h1><div class
         <span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">deletion</span> <span class="o">=</span> <span class="kc">False</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">predictions</span> <span class="o">=</span> <span class="p">{}</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">num_iterations_per_kernel</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">divisors</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">|</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
 
 <div class="viewcode-block" id="AISEDetection.generate_saliency_map">
 <a class="viewcode-back" href="../../../../../api-manual.html#openvino_xai.methods.AISEDetection.generate_saliency_map">[docs]</a>

releases/1.1.0/_modules/openvino_xai/methods/black_box/rise.html

@@ -444,6 +444,8 @@ <h1>Source code for openvino_xai.methods.black_box.rise</h1><div class="highligh
         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
             <span class="n">model</span><span class="o">=</span><span class="n">model</span><span class="p">,</span> <span class="n">postprocess_fn</span><span class="o">=</span><span class="n">postprocess_fn</span><span class="p">,</span> <span class="n">preprocess_fn</span><span class="o">=</span><span class="n">preprocess_fn</span><span class="p">,</span> <span class="n">device_name</span><span class="o">=</span><span class="n">device_name</span>
         <span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">num_masks</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">num_cells</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
 
         <span class="k">if</span> <span class="n">prepare_model</span><span class="p">:</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">prepare_model</span><span class="p">()</span>
@@ -485,13 +487,11 @@ <h1>Source code for openvino_xai.methods.black_box.rise</h1><div class="highligh
 <span class="sd">        &quot;&quot;&quot;</span>
         <span class="n">data_preprocessed</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">preprocess_fn</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
 
-        <span class="n">num_masks</span><span class="p">,</span> <span class="n">num_cells</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_preset_parameters</span><span class="p">(</span><span class="n">preset</span><span class="p">,</span> <span class="n">num_masks</span><span class="p">,</span> <span class="n">num_cells</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">num_masks</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_cells</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_preset_parameters</span><span class="p">(</span><span class="n">preset</span><span class="p">,</span> <span class="n">num_masks</span><span class="p">,</span> <span class="n">num_cells</span><span class="p">)</span>
 
         <span class="n">saliency_maps</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_run_synchronous_explanation</span><span class="p">(</span>
             <span class="n">data_preprocessed</span><span class="p">,</span>
             <span class="n">target_indices</span><span class="p">,</span>
-            <span class="n">num_masks</span><span class="p">,</span>
-            <span class="n">num_cells</span><span class="p">,</span>
             <span class="n">prob</span><span class="p">,</span>
             <span class="n">seed</span><span class="p">,</span>
         <span class="p">)</span>
@@ -536,8 +536,6 @@ <h1>Source code for openvino_xai.methods.black_box.rise</h1><div class="highligh
         <span class="bp">self</span><span class="p">,</span>
         <span class="n">data_preprocessed</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span>
         <span class="n">target_classes</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">num_masks</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
-        <span class="n">num_cells</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
         <span class="n">prob</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
         <span class="n">seed</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
@@ -554,8 +552,8 @@ <h1>Source code for openvino_xai.methods.black_box.rise</h1><div class="highligh
         <span class="n">rand_generator</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">default_rng</span><span class="p">(</span><span class="n">seed</span><span class="o">=</span><span class="n">seed</span><span class="p">)</span>
 
         <span class="n">saliency_maps</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">num_targets</span><span class="p">,</span> <span class="n">input_size</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">input_size</span><span class="p">[</span><span class="mi">1</span><span class="p">]))</span>
-        <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="n">tqdm</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">num_masks</span><span class="p">),</span> <span class="n">desc</span><span class="o">=</span><span class="s2">&quot;Explaining in synchronous mode&quot;</span><span class="p">):</span>
-            <span class="n">mask</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_generate_mask</span><span class="p">(</span><span class="n">input_size</span><span class="p">,</span> <span class="n">num_cells</span><span class="p">,</span> <span class="n">prob</span><span class="p">,</span> <span class="n">rand_generator</span><span class="p">)</span>
+        <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="n">tqdm</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_masks</span><span class="p">),</span> <span class="n">desc</span><span class="o">=</span><span class="s2">&quot;Explaining in synchronous mode&quot;</span><span class="p">):</span>
+            <span class="n">mask</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_generate_mask</span><span class="p">(</span><span class="n">input_size</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_cells</span><span class="p">,</span> <span class="n">prob</span><span class="p">,</span> <span class="n">rand_generator</span><span class="p">)</span>
             <span class="c1"># Add channel dimensions for masks</span>
             <span class="k">if</span> <span class="n">is_bhwc_layout</span><span class="p">(</span><span class="n">data_preprocessed</span><span class="p">):</span>
                 <span class="n">masked</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">expand_dims</span><span class="p">(</span><span class="n">mask</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> <span class="o">*</span> <span class="n">data_preprocessed</span>