From d1bd0b3f12a89727fe08030d4ddbef0e7ad6f2f6 Mon Sep 17 00:00:00 2001
From: raphaelDkhn <raphael@gizatech.xyz>
Date: Mon, 22 Jan 2024 15:33:22 +0200
Subject: [PATCH] update osiris version

---
 poetry.lock         | 8 ++++----
 pyproject.toml      | 2 +-
 tests/test_model.py | 2 +-
 3 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index d48662e..8d260bd 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -821,13 +821,13 @@ types-requests = ">=2.31.0.2,<3.0.0.0"
 
 [[package]]
 name = "giza-osiris"
-version = "0.1.8"
+version = "0.2.0"
 description = "Osiris is a Python library designed for efficient data conversion and management, primarily transforming data into Cairo programs"
 optional = false
 python-versions = ">=3.11,<4.0"
 files = [
-    {file = "giza_osiris-0.1.8-py3-none-any.whl", hash = "sha256:c8a4ad26ed33d472f58d85e3ad39c8122dfe86f5809272ce9ce9c9c0bf7ecc9f"},
-    {file = "giza_osiris-0.1.8.tar.gz", hash = "sha256:fd9d9f37d158b6c6d368ecee09528f55c47e3968479e03fab4aa9262fc9761aa"},
+    {file = "giza_osiris-0.2.0-py3-none-any.whl", hash = "sha256:a0b188e238347e2a831bdd651a0cf4f7f0bac95128cc9219b719e3008272568d"},
+    {file = "giza_osiris-0.2.0.tar.gz", hash = "sha256:fca7baf56e237887568c1a65d3b8d3496a77c913e8aa0d03db6289400c308269"},
 ]
 
 [package.dependencies]
@@ -3745,4 +3745,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.11,<4.0"
-content-hash = "66d1d3daf055ee80ab1cce1a47967d616c1e9da4e498f92734db4c793a87f03c"
+content-hash = "c525ce4829c7bd0d9e49cf5267a51c8bbdf5548b3b394ccdf5d33e00c0a83933"
diff --git a/pyproject.toml b/pyproject.toml
index 58dd203..26db2ad 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -18,7 +18,7 @@ pyyaml = "^6.0.1"
 prefect-docker = "^0.4.1"
 giza-cli = "^0.6.0"
 distlib = "^0.3.8"
-giza-osiris = "0.1.8"
+giza-osiris = "0.2.0"
 
 [tool.poetry.dev-dependencies]
 pytest = "^6.2.5"
diff --git a/tests/test_model.py b/tests/test_model.py
index a725759..826c3b3 100644
--- a/tests/test_model.py
+++ b/tests/test_model.py
@@ -12,6 +12,6 @@ def test_predict_success():
     arr = np.array([[1, 2], [3, 4]], dtype=np.uint32)
 
     result = model.predict(
-        input_feed={"arr_1": arr}, verifiable=True, output_dtype='tensor_uint')
+        input_feed={"arr_1": arr}, verifiable=True, output_dtype='tensor_int')
 
     assert np.array_equal(result, arr)