Delete correct_classifier_conv1d.mlmodelc

correct_classifier_conv1d.mlmodelc/analytics/coremldata.bin

@@ -1,3 +0,0 @@
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-size 263

correct_classifier_conv1d.mlmodelc/coremldata.bin

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correct_classifier_conv1d.mlmodelc/metadata.json

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-[
-  {
-    "metadataOutputVersion" : "3.0",
-    "storagePrecision" : "Float16",
-    "outputSchema" : [
-      {
-        "hasShapeFlexibility" : "0",
-        "isOptional" : "0",
-        "dataType" : "Float32",
-        "formattedType" : "MultiArray (Float32 1 × 1)",
-        "shortDescription" : "",
-        "shape" : "[1, 1]",
-        "name" : "vad_probability",
-        "type" : "MultiArray"
-      }
-    ],
-    "modelParameters" : [
-
-    ],
-    "specificationVersion" : 6,
-    "mlProgramOperationTypeHistogram" : {
-      "Cast" : 2,
-      "Conv" : 1,
-      "SliceByIndex" : 1,
-      "Transpose" : 1,
-      "Relu" : 1,
-      "Sigmoid" : 1,
-      "Squeeze" : 1
-    },
-    "computePrecision" : "Mixed (Float16, Float32, Int32)",
-    "isUpdatable" : "0",
-    "stateSchema" : [
-
-    ],
-    "availability" : {
-      "macOS" : "12.0",
-      "tvOS" : "15.0",
-      "visionOS" : "1.0",
-      "watchOS" : "8.0",
-      "iOS" : "15.0",
-      "macCatalyst" : "15.0"
-    },
-    "modelType" : {
-      "name" : "MLModelType_mlProgram"
-    },
-    "userDefinedMetadata" : {
-      "com.github.apple.coremltools.version" : "7.2",
-      "com.github.apple.coremltools.source" : "torch==2.7.1",
-      "com.github.apple.coremltools.source_dialect" : "TorchScript"
-    },
-    "inputSchema" : [
-      {
-        "hasShapeFlexibility" : "0",
-        "isOptional" : "0",
-        "dataType" : "Float32",
-        "formattedType" : "MultiArray (Float32 1 × 4 × 128)",
-        "shortDescription" : "",
-        "shape" : "[1, 4, 128]",
-        "name" : "rnn_features",
-        "type" : "MultiArray"
-      }
-    ],
-    "generatedClassName" : "correct_classifier_conv1d",
-    "method" : "predict"
-  }
-]

correct_classifier_conv1d.mlmodelc/model.mil

@@ -1,28 +0,0 @@
-program(1.0)
-[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3405.2.1"}, {"coremlc-version", "3404.23.1"}, {"coremltools-component-torch", "2.7.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.2"}})]
-{
-    func main<ios15>(tensor<fp32, [1, 4, 128]> rnn_features) {
-            tensor<int32, [3]> input_1_perm_0 = const()[name = tensor<string, []>("input_1_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
-            tensor<string, []> rnn_features_to_fp16_dtype_0 = const()[name = tensor<string, []>("rnn_features_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
-            tensor<fp16, [1, 4, 128]> cast_1 = cast(dtype = rnn_features_to_fp16_dtype_0, x = rnn_features)[name = tensor<string, []>("cast_1")];
-            tensor<fp16, [1, 128, 4]> transpose_0 = transpose(perm = input_1_perm_0, x = cast_1)[name = tensor<string, []>("transpose_0")];
-            tensor<fp16, [1, 128, 4]> input_5_cast_fp16 = relu(x = transpose_0)[name = tensor<string, []>("input_5_cast_fp16")];
-            tensor<int32, []> var_13 = const()[name = tensor<string, []>("op_13"), val = tensor<int32, []>(1)];
-            tensor<int32, [1]> var_16 = const()[name = tensor<string, []>("op_16"), val = tensor<int32, [1]>([1])];
-            tensor<int32, [1]> var_18 = const()[name = tensor<string, []>("op_18"), val = tensor<int32, [1]>([1])];
-            tensor<string, []> x_3_pad_type_0 = const()[name = tensor<string, []>("x_3_pad_type_0"), val = tensor<string, []>("custom")];
-            tensor<int32, [2]> x_3_pad_0 = const()[name = tensor<string, []>("x_3_pad_0"), val = tensor<int32, [2]>([0, 0])];
-            tensor<fp16, [1, 128, 1]> classifier_weight_to_fp16 = const()[name = tensor<string, []>("classifier_weight_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
-            tensor<fp16, [1]> classifier_bias_to_fp16 = const()[name = tensor<string, []>("classifier_bias_to_fp16"), val = tensor<fp16, [1]>([-0x1.868p-3])];
-            tensor<fp16, [1, 1, 4]> x_3_cast_fp16 = conv(bias = classifier_bias_to_fp16, dilations = var_18, groups = var_13, pad = x_3_pad_0, pad_type = x_3_pad_type_0, strides = var_16, weight = classifier_weight_to_fp16, x = input_5_cast_fp16)[name = tensor<string, []>("x_3_cast_fp16")];
-            tensor<int32, [1]> x_axes_0 = const()[name = tensor<string, []>("x_axes_0"), val = tensor<int32, [1]>([1])];
-            tensor<fp16, [1, 4]> x_cast_fp16 = squeeze(axes = x_axes_0, x = x_3_cast_fp16)[name = tensor<string, []>("x_cast_fp16")];
-            tensor<int32, [2]> input_begin_0 = const()[name = tensor<string, []>("input_begin_0"), val = tensor<int32, [2]>([0, -1])];
-            tensor<int32, [2]> input_end_0 = const()[name = tensor<string, []>("input_end_0"), val = tensor<int32, [2]>([1, 4])];
-            tensor<bool, [2]> input_end_mask_0 = const()[name = tensor<string, []>("input_end_mask_0"), val = tensor<bool, [2]>([true, true])];
-            tensor<fp16, [1, 1]> input_cast_fp16 = slice_by_index(begin = input_begin_0, end = input_end_0, end_mask = input_end_mask_0, x = x_cast_fp16)[name = tensor<string, []>("input_cast_fp16")];
-            tensor<fp16, [1, 1]> var_33_cast_fp16 = sigmoid(x = input_cast_fp16)[name = tensor<string, []>("op_33_cast_fp16")];
-            tensor<string, []> var_33_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("op_33_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
-            tensor<fp32, [1, 1]> vad_probability = cast(dtype = var_33_cast_fp16_to_fp32_dtype_0, x = var_33_cast_fp16)[name = tensor<string, []>("cast_0")];
-        } -> (vad_probability);
-}

correct_classifier_conv1d.mlmodelc/weights/weight.bin

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
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