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Runtime error
Runtime error
Alex Cabrera
commited on
Commit
•
5dbce8b
1
Parent(s):
e836fc3
v4
Browse files- .zeno_cache/OUTPUTStable Diffusion.pickle +3 -0
- .zeno_cache/PREDISTILLlength.pickle +2 -2
- .zeno_cache/folders.pickle +3 -0
- .zeno_cache/reports.pickle +3 -0
- .zeno_cache/slices.pickle +3 -0
- .zeno_cache/view.mjs +6 -11
- __pycache__/functions.cpython-38.pyc +0 -0
- config.toml +8 -2
- functions.py +21 -4
- requirements.txt +1 -1
.zeno_cache/OUTPUTStable Diffusion.pickle
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:a7dae3bfa1cc6f8430415a422c96a48866c8bd7ef3e849e193349bd9b29f15c8
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size 106025883
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.zeno_cache/PREDISTILLlength.pickle
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@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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-
size
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:4df3b80eda5266afa2f990fb20fc79a754d0a5ef766c8f25df19542a018a3b7d
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size 100459898
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.zeno_cache/folders.pickle
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version https://git-lfs.github.com/spec/v1
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oid sha256:ec0a6ccf9debf1c16781445c4b9106080d00478b0559469336db7c7b7b9711c8
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size 5
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.zeno_cache/reports.pickle
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version https://git-lfs.github.com/spec/v1
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oid sha256:a848f603456d7c6c08a6072a4d67f7bafe742b9a670496c51e06883f12943058
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size 1625
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.zeno_cache/slices.pickle
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version https://git-lfs.github.com/spec/v1
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oid sha256:4749f80758f2a5d004c27f8aadbbb0d6aaf286f338c2a5e0f4f726d9cb3bbf90
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size 801
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.zeno_cache/view.mjs
CHANGED
@@ -533,7 +533,7 @@ function add_css(target) {
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append_styles(target, "svelte-8lajst", ".label.svelte-8lajst{margin-right:5px;font-size:10px;color:rgba(0, 0, 0, 0.5);font-variant:small-caps}.text.svelte-8lajst{display:flex;flex-direction:row}.value.svelte-8lajst{font-size:10px}.box.svelte-8lajst{width:min-content;padding:5px;border:0.5px solid rgb(224, 224, 224)}");
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}
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// (
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function create_if_block(ctx) {
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let div;
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let span0;
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@@ -650,7 +650,7 @@ function create_fragment(ctx) {
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this.h();
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},
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h() {
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if (!src_url_equal(img.src, img_src_value =
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attr(img, "alt", img_alt_value = "Image thumbnail for instance " + /*entry*/ ctx[0][/*idColumn*/ ctx[4]]);
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set_style(img, "max-width", `200px`, false);
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attr(span0, "class", "label svelte-8lajst");
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@@ -675,7 +675,7 @@ function create_fragment(ctx) {
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if (if_block) if_block.m(div1, null);
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},
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p(ctx, [dirty]) {
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if (dirty & /*
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attr(img, "src", img_src_value);
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}
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@@ -713,7 +713,6 @@ function instance($$self, $$props, $$invalidate) {
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let { modelColumn } = $$props;
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let { labelColumn } = $$props;
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let { dataColumn } = $$props;
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let { dataOrigin } = $$props;
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let { idColumn } = $$props;
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$$self.$$set = $$props => {
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@@ -721,12 +720,11 @@ function instance($$self, $$props, $$invalidate) {
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if ('options' in $$props) $$invalidate(5, options = $$props.options);
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if ('modelColumn' in $$props) $$invalidate(1, modelColumn = $$props.modelColumn);
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if ('labelColumn' in $$props) $$invalidate(2, labelColumn = $$props.labelColumn);
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-
if ('dataColumn' in $$props) $$invalidate(
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if ('dataOrigin' in $$props) $$invalidate(3, dataOrigin = $$props.dataOrigin);
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if ('idColumn' in $$props) $$invalidate(4, idColumn = $$props.idColumn);
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};
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return [entry, modelColumn, labelColumn,
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}
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class InstanceView extends SvelteComponent {
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options: 5,
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modelColumn: 1,
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labelColumn: 2,
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dataColumn:
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dataOrigin: 3,
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idColumn: 4
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},
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add_css
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modelColumn,
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labelColumn,
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dataColumn,
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dataOrigin,
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idColumn
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) {
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new InstanceView({
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modelColumn: modelColumn,
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labelColumn: labelColumn,
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dataColumn: dataColumn,
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dataOrigin: dataOrigin,
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idColumn: idColumn,
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},
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hydrate: true,
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append_styles(target, "svelte-8lajst", ".label.svelte-8lajst{margin-right:5px;font-size:10px;color:rgba(0, 0, 0, 0.5);font-variant:small-caps}.text.svelte-8lajst{display:flex;flex-direction:row}.value.svelte-8lajst{font-size:10px}.box.svelte-8lajst{width:min-content;padding:5px;border:0.5px solid rgb(224, 224, 224)}");
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}
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+
// (21:2) {#if modelColumn && entry[modelColumn]}
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function create_if_block(ctx) {
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let div;
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let span0;
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this.h();
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},
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h() {
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if (!src_url_equal(img.src, img_src_value = /*entry*/ ctx[0][/*dataColumn*/ ctx[3]])) attr(img, "src", img_src_value);
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attr(img, "alt", img_alt_value = "Image thumbnail for instance " + /*entry*/ ctx[0][/*idColumn*/ ctx[4]]);
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set_style(img, "max-width", `200px`, false);
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attr(span0, "class", "label svelte-8lajst");
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if (if_block) if_block.m(div1, null);
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},
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p(ctx, [dirty]) {
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if (dirty & /*entry, dataColumn*/ 9 && !src_url_equal(img.src, img_src_value = /*entry*/ ctx[0][/*dataColumn*/ ctx[3]])) {
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attr(img, "src", img_src_value);
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}
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let { modelColumn } = $$props;
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let { labelColumn } = $$props;
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let { dataColumn } = $$props;
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let { idColumn } = $$props;
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$$self.$$set = $$props => {
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if ('options' in $$props) $$invalidate(5, options = $$props.options);
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if ('modelColumn' in $$props) $$invalidate(1, modelColumn = $$props.modelColumn);
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if ('labelColumn' in $$props) $$invalidate(2, labelColumn = $$props.labelColumn);
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if ('dataColumn' in $$props) $$invalidate(3, dataColumn = $$props.dataColumn);
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if ('idColumn' in $$props) $$invalidate(4, idColumn = $$props.idColumn);
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};
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return [entry, modelColumn, labelColumn, dataColumn, idColumn, options];
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}
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class InstanceView extends SvelteComponent {
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options: 5,
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modelColumn: 1,
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labelColumn: 2,
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dataColumn: 3,
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idColumn: 4
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},
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add_css
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modelColumn,
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labelColumn,
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dataColumn,
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idColumn
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) {
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new InstanceView({
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modelColumn: modelColumn,
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labelColumn: labelColumn,
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dataColumn: dataColumn,
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idColumn: idColumn,
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},
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hydrate: true,
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__pycache__/functions.cpython-38.pyc
ADDED
Binary file (1.19 kB). View file
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config.toml
CHANGED
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functions = "./"
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view = "image-classification"
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metadata = "./metadata_f.parquet"
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data_path = "https://diffusiondb.m4ke.org/"
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data_column = "image_name"
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label_column = "prompt"
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batch_size = 100000
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-
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host = "0.0.0.0"
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editable = false
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functions = "./"
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view = "image-classification"
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metadata = "./metadata_f.parquet"
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models = ["Stable Diffusion"]
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data_path = "https://diffusiondb.m4ke.org/"
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data_column = "image_name"
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id_column = "image_name"
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label_column = "prompt"
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batch_size = 100000
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calculate_histogram_metrics = false
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port = 7860
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host = "0.0.0.0"
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editable = false
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# host = "localhost"
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# editable = true
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functions.py
CHANGED
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from zeno import distill, metric, ZenoOptions
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from pandas import DataFrame
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@distill
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def length(df: DataFrame, ops: ZenoOptions):
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return df["prompt"].str.len()
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@metric
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def avg_image_nswf(df: DataFrame, ops: ZenoOptions):
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return float(df["image_nsfw"].dropna().mean())
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@metric
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def avg_prompt_nsfw(df: DataFrame, ops: ZenoOptions):
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return float(df["prompt_nsfw"].dropna().mean())
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from pandas import DataFrame
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from zeno import (
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DistillReturn,
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MetricReturn,
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ModelReturn,
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ZenoOptions,
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distill,
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metric,
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model,
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)
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@model
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def model_ret(name):
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def model(df: DataFrame, ops: ZenoOptions):
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return ModelReturn(model_output=df[ops.data_column])
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return model
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@distill
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def length(df: DataFrame, ops: ZenoOptions):
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return DistillReturn(distill_output=df["prompt"].str.len())
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@metric
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def avg_image_nswf(df: DataFrame, ops: ZenoOptions):
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return MetricReturn(metric=float(df["image_nsfw"].dropna().mean()))
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@metric
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def avg_prompt_nsfw(df: DataFrame, ops: ZenoOptions):
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return MetricReturn(metric=float(df["prompt_nsfw"].dropna().mean()))
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requirements.txt
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zenoml>=0.
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pyarrow
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zenoml>=0.4.6
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pyarrow
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