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ckpts/universal/global_step80/zero/15.attention.query_key_value.weight/exp_avg.pt

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ckpts/universal/global_step80/zero/15.attention.query_key_value.weight/exp_avg_sq.pt

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+size 50332843

ckpts/universal/global_step80/zero/15.attention.query_key_value.weight/fp32.pt

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ckpts/universal/global_step80/zero/22.mlp.dense_h_to_4h.weight/exp_avg.pt

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ckpts/universal/global_step80/zero/22.mlp.dense_h_to_4h.weight/fp32.pt

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venv/lib/python3.10/site-packages/pandas/tests/indexes/datetimes/methods/test_asof.py

@@ -0,0 +1,30 @@
+from datetime import timedelta
+
+from pandas import (
+    Index,
+    Timestamp,
+    date_range,
+    isna,
+)
+
+
+class TestAsOf:
+    def test_asof_partial(self):
+        index = date_range("2010-01-01", periods=2, freq="ME")
+        expected = Timestamp("2010-02-28")
+        result = index.asof("2010-02")
+        assert result == expected
+        assert not isinstance(result, Index)
+
+    def test_asof(self):
+        index = date_range("2020-01-01", periods=10)
+
+        dt = index[0]
+        assert index.asof(dt) == dt
+        assert isna(index.asof(dt - timedelta(1)))
+
+        dt = index[-1]
+        assert index.asof(dt + timedelta(1)) == dt
+
+        dt = index[0].to_pydatetime()
+        assert isinstance(index.asof(dt), Timestamp)

venv/lib/python3.10/site-packages/pandas/tests/indexes/datetimes/methods/test_astype.py

@@ -0,0 +1,335 @@
+from datetime import datetime
+
+import dateutil
+import numpy as np
+import pytest
+import pytz
+
+import pandas as pd
+from pandas import (
+    DatetimeIndex,
+    Index,
+    NaT,
+    PeriodIndex,
+    Timestamp,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestDatetimeIndex:
+    @pytest.mark.parametrize("tzstr", ["US/Eastern", "dateutil/US/Eastern"])
+    def test_dti_astype_asobject_around_dst_transition(self, tzstr):
+        # GH#1345
+
+        # dates around a dst transition
+        rng = date_range("2/13/2010", "5/6/2010", tz=tzstr)
+
+        objs = rng.astype(object)
+        for i, x in enumerate(objs):
+            exval = rng[i]
+            assert x == exval
+            assert x.tzinfo == exval.tzinfo
+
+        objs = rng.astype(object)
+        for i, x in enumerate(objs):
+            exval = rng[i]
+            assert x == exval
+            assert x.tzinfo == exval.tzinfo
+
+    def test_astype(self):
+        # GH 13149, GH 13209
+        idx = DatetimeIndex(
+            ["2016-05-16", "NaT", NaT, np.nan], dtype="M8[ns]", name="idx"
+        )
+
+        result = idx.astype(object)
+        expected = Index(
+            [Timestamp("2016-05-16")] + [NaT] * 3, dtype=object, name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+
+        result = idx.astype(np.int64)
+        expected = Index(
+            [1463356800000000000] + [-9223372036854775808] * 3,
+            dtype=np.int64,
+            name="idx",
+        )
+        tm.assert_index_equal(result, expected)
+
+    def test_astype2(self):
+        rng = date_range("1/1/2000", periods=10, name="idx")
+        result = rng.astype("i8")
+        tm.assert_index_equal(result, Index(rng.asi8, name="idx"))
+        tm.assert_numpy_array_equal(result.values, rng.asi8)
+
+    def test_astype_uint(self):
+        arr = date_range("2000", periods=2, name="idx")
+
+        with pytest.raises(TypeError, match=r"Do obj.astype\('int64'\)"):
+            arr.astype("uint64")
+        with pytest.raises(TypeError, match=r"Do obj.astype\('int64'\)"):
+            arr.astype("uint32")
+
+    def test_astype_with_tz(self):
+        # with tz
+        rng = date_range("1/1/2000", periods=10, tz="US/Eastern")
+        msg = "Cannot use .astype to convert from timezone-aware"
+        with pytest.raises(TypeError, match=msg):
+            # deprecated
+            rng.astype("datetime64[ns]")
+        with pytest.raises(TypeError, match=msg):
+            # check DatetimeArray while we're here deprecated
+            rng._data.astype("datetime64[ns]")
+
+    def test_astype_tzaware_to_tzaware(self):
+        # GH 18951: tz-aware to tz-aware
+        idx = date_range("20170101", periods=4, tz="US/Pacific")
+        result = idx.astype("datetime64[ns, US/Eastern]")
+        expected = date_range("20170101 03:00:00", periods=4, tz="US/Eastern")
+        tm.assert_index_equal(result, expected)
+        assert result.freq == expected.freq
+
+    def test_astype_tznaive_to_tzaware(self):
+        # GH 18951: tz-naive to tz-aware
+        idx = date_range("20170101", periods=4)
+        idx = idx._with_freq(None)  # tz_localize does not preserve freq
+        msg = "Cannot use .astype to convert from timezone-naive"
+        with pytest.raises(TypeError, match=msg):
+            # dt64->dt64tz deprecated
+            idx.astype("datetime64[ns, US/Eastern]")
+        with pytest.raises(TypeError, match=msg):
+            # dt64->dt64tz deprecated
+            idx._data.astype("datetime64[ns, US/Eastern]")
+
+    def test_astype_str_nat(self):
+        # GH 13149, GH 13209
+        # verify that we are returning NaT as a string (and not unicode)
+
+        idx = DatetimeIndex(["2016-05-16", "NaT", NaT, np.nan])
+        result = idx.astype(str)
+        expected = Index(["2016-05-16", "NaT", "NaT", "NaT"], dtype=object)
+        tm.assert_index_equal(result, expected)
+
+    def test_astype_str(self):
+        # test astype string - #10442
+        dti = date_range("2012-01-01", periods=4, name="test_name")
+        result = dti.astype(str)
+        expected = Index(
+            ["2012-01-01", "2012-01-02", "2012-01-03", "2012-01-04"],
+            name="test_name",
+            dtype=object,
+        )
+        tm.assert_index_equal(result, expected)
+
+    def test_astype_str_tz_and_name(self):
+        # test astype string with tz and name
+        dti = date_range("2012-01-01", periods=3, name="test_name", tz="US/Eastern")
+        result = dti.astype(str)
+        expected = Index(
+            [
+                "2012-01-01 00:00:00-05:00",
+                "2012-01-02 00:00:00-05:00",
+                "2012-01-03 00:00:00-05:00",
+            ],
+            name="test_name",
+            dtype=object,
+        )
+        tm.assert_index_equal(result, expected)
+
+    def test_astype_str_freq_and_name(self):
+        # test astype string with freqH and name
+        dti = date_range("1/1/2011", periods=3, freq="h", name="test_name")
+        result = dti.astype(str)
+        expected = Index(
+            ["2011-01-01 00:00:00", "2011-01-01 01:00:00", "2011-01-01 02:00:00"],
+            name="test_name",
+            dtype=object,
+        )
+        tm.assert_index_equal(result, expected)
+
+    def test_astype_str_freq_and_tz(self):
+        # test astype string with freqH and timezone
+        dti = date_range(
+            "3/6/2012 00:00", periods=2, freq="h", tz="Europe/London", name="test_name"
+        )
+        result = dti.astype(str)
+        expected = Index(
+            ["2012-03-06 00:00:00+00:00", "2012-03-06 01:00:00+00:00"],
+            dtype=object,
+            name="test_name",
+        )
+        tm.assert_index_equal(result, expected)
+
+    def test_astype_datetime64(self):
+        # GH 13149, GH 13209
+        idx = DatetimeIndex(
+            ["2016-05-16", "NaT", NaT, np.nan], dtype="M8[ns]", name="idx"
+        )
+
+        result = idx.astype("datetime64[ns]")
+        tm.assert_index_equal(result, idx)
+        assert result is not idx
+
+        result = idx.astype("datetime64[ns]", copy=False)
+        tm.assert_index_equal(result, idx)
+        assert result is idx
+
+        idx_tz = DatetimeIndex(["2016-05-16", "NaT", NaT, np.nan], tz="EST", name="idx")
+        msg = "Cannot use .astype to convert from timezone-aware"
+        with pytest.raises(TypeError, match=msg):
+            # dt64tz->dt64 deprecated
+            result = idx_tz.astype("datetime64[ns]")
+
+    def test_astype_object(self):
+        rng = date_range("1/1/2000", periods=20)
+
+        casted = rng.astype("O")
+        exp_values = list(rng)
+
+        tm.assert_index_equal(casted, Index(exp_values, dtype=np.object_))
+        assert casted.tolist() == exp_values
+
+    @pytest.mark.parametrize("tz", [None, "Asia/Tokyo"])
+    def test_astype_object_tz(self, tz):
+        idx = date_range(start="2013-01-01", periods=4, freq="ME", name="idx", tz=tz)
+        expected_list = [
+            Timestamp("2013-01-31", tz=tz),
+            Timestamp("2013-02-28", tz=tz),
+            Timestamp("2013-03-31", tz=tz),
+            Timestamp("2013-04-30", tz=tz),
+        ]
+        expected = Index(expected_list, dtype=object, name="idx")
+        result = idx.astype(object)
+        tm.assert_index_equal(result, expected)
+        assert idx.tolist() == expected_list
+
+    def test_astype_object_with_nat(self):
+        idx = DatetimeIndex(
+            [datetime(2013, 1, 1), datetime(2013, 1, 2), NaT, datetime(2013, 1, 4)],
+            name="idx",
+        )
+        expected_list = [
+            Timestamp("2013-01-01"),
+            Timestamp("2013-01-02"),
+            NaT,
+            Timestamp("2013-01-04"),
+        ]
+        expected = Index(expected_list, dtype=object, name="idx")
+        result = idx.astype(object)
+        tm.assert_index_equal(result, expected)
+        assert idx.tolist() == expected_list
+
+    @pytest.mark.parametrize(
+        "dtype",
+        [float, "timedelta64", "timedelta64[ns]", "datetime64", "datetime64[D]"],
+    )
+    def test_astype_raises(self, dtype):
+        # GH 13149, GH 13209
+        idx = DatetimeIndex(["2016-05-16", "NaT", NaT, np.nan])
+        msg = "Cannot cast DatetimeIndex to dtype"
+        if dtype == "datetime64":
+            msg = "Casting to unit-less dtype 'datetime64' is not supported"
+        with pytest.raises(TypeError, match=msg):
+            idx.astype(dtype)
+
+    def test_index_convert_to_datetime_array(self):
+        def _check_rng(rng):
+            converted = rng.to_pydatetime()
+            assert isinstance(converted, np.ndarray)
+            for x, stamp in zip(converted, rng):
+                assert isinstance(x, datetime)
+                assert x == stamp.to_pydatetime()
+                assert x.tzinfo == stamp.tzinfo
+
+        rng = date_range("20090415", "20090519")
+        rng_eastern = date_range("20090415", "20090519", tz="US/Eastern")
+        rng_utc = date_range("20090415", "20090519", tz="utc")
+
+        _check_rng(rng)
+        _check_rng(rng_eastern)
+        _check_rng(rng_utc)
+
+    def test_index_convert_to_datetime_array_explicit_pytz(self):
+        def _check_rng(rng):
+            converted = rng.to_pydatetime()
+            assert isinstance(converted, np.ndarray)
+            for x, stamp in zip(converted, rng):
+                assert isinstance(x, datetime)
+                assert x == stamp.to_pydatetime()
+                assert x.tzinfo == stamp.tzinfo
+
+        rng = date_range("20090415", "20090519")
+        rng_eastern = date_range("20090415", "20090519", tz=pytz.timezone("US/Eastern"))
+        rng_utc = date_range("20090415", "20090519", tz=pytz.utc)
+
+        _check_rng(rng)
+        _check_rng(rng_eastern)
+        _check_rng(rng_utc)
+
+    def test_index_convert_to_datetime_array_dateutil(self):
+        def _check_rng(rng):
+            converted = rng.to_pydatetime()
+            assert isinstance(converted, np.ndarray)
+            for x, stamp in zip(converted, rng):
+                assert isinstance(x, datetime)
+                assert x == stamp.to_pydatetime()
+                assert x.tzinfo == stamp.tzinfo
+
+        rng = date_range("20090415", "20090519")
+        rng_eastern = date_range("20090415", "20090519", tz="dateutil/US/Eastern")
+        rng_utc = date_range("20090415", "20090519", tz=dateutil.tz.tzutc())
+
+        _check_rng(rng)
+        _check_rng(rng_eastern)
+        _check_rng(rng_utc)
+
+    @pytest.mark.parametrize(
+        "tz, dtype",
+        [["US/Pacific", "datetime64[ns, US/Pacific]"], [None, "datetime64[ns]"]],
+    )
+    def test_integer_index_astype_datetime(self, tz, dtype):
+        # GH 20997, 20964, 24559
+        val = [Timestamp("2018-01-01", tz=tz).as_unit("ns")._value]
+        result = Index(val, name="idx").astype(dtype)
+        expected = DatetimeIndex(["2018-01-01"], tz=tz, name="idx").as_unit("ns")
+        tm.assert_index_equal(result, expected)
+
+    def test_dti_astype_period(self):
+        idx = DatetimeIndex([NaT, "2011-01-01", "2011-02-01"], name="idx")
+
+        res = idx.astype("period[M]")
+        exp = PeriodIndex(["NaT", "2011-01", "2011-02"], freq="M", name="idx")
+        tm.assert_index_equal(res, exp)
+
+        res = idx.astype("period[3M]")
+        exp = PeriodIndex(["NaT", "2011-01", "2011-02"], freq="3M", name="idx")
+        tm.assert_index_equal(res, exp)
+
+
+class TestAstype:
+    @pytest.mark.parametrize("tz", [None, "US/Central"])
+    def test_astype_category(self, tz):
+        obj = date_range("2000", periods=2, tz=tz, name="idx")
+        result = obj.astype("category")
+        dti = DatetimeIndex(["2000-01-01", "2000-01-02"], tz=tz).as_unit("ns")
+        expected = pd.CategoricalIndex(
+            dti,
+            name="idx",
+        )
+        tm.assert_index_equal(result, expected)
+
+        result = obj._data.astype("category")
+        expected = expected.values
+        tm.assert_categorical_equal(result, expected)
+
+    @pytest.mark.parametrize("tz", [None, "US/Central"])
+    def test_astype_array_fallback(self, tz):
+        obj = date_range("2000", periods=2, tz=tz, name="idx")
+        result = obj.astype(bool)
+        expected = Index(np.array([True, True]), name="idx")
+        tm.assert_index_equal(result, expected)
+
+        result = obj._data.astype(bool)
+        expected = np.array([True, True])
+        tm.assert_numpy_array_equal(result, expected)

venv/lib/python3.10/site-packages/pandas/tests/indexes/datetimes/methods/test_delete.py

@@ -0,0 +1,141 @@
+import pytest
+
+from pandas import (
+    DatetimeIndex,
+    Series,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestDelete:
+    def test_delete(self, unit):
+        idx = date_range(
+            start="2000-01-01", periods=5, freq="ME", name="idx", unit=unit
+        )
+
+        # preserve freq
+        expected_0 = date_range(
+            start="2000-02-01", periods=4, freq="ME", name="idx", unit=unit
+        )
+        expected_4 = date_range(
+            start="2000-01-01", periods=4, freq="ME", name="idx", unit=unit
+        )
+
+        # reset freq to None
+        expected_1 = DatetimeIndex(
+            ["2000-01-31", "2000-03-31", "2000-04-30", "2000-05-31"],
+            freq=None,
+            name="idx",
+        ).as_unit(unit)
+
+        cases = {
+            0: expected_0,
+            -5: expected_0,
+            -1: expected_4,
+            4: expected_4,
+            1: expected_1,
+        }
+        for n, expected in cases.items():
+            result = idx.delete(n)
+            tm.assert_index_equal(result, expected)
+            assert result.name == expected.name
+            assert result.freq == expected.freq
+
+        with pytest.raises((IndexError, ValueError), match="out of bounds"):
+            # either depending on numpy version
+            idx.delete(5)
+
+    @pytest.mark.parametrize("tz", [None, "Asia/Tokyo", "US/Pacific"])
+    def test_delete2(self, tz):
+        idx = date_range(
+            start="2000-01-01 09:00", periods=10, freq="h", name="idx", tz=tz
+        )
+
+        expected = date_range(
+            start="2000-01-01 10:00", periods=9, freq="h", name="idx", tz=tz
+        )
+        result = idx.delete(0)
+        tm.assert_index_equal(result, expected)
+        assert result.name == expected.name
+        assert result.freqstr == "h"
+        assert result.tz == expected.tz
+
+        expected = date_range(
+            start="2000-01-01 09:00", periods=9, freq="h", name="idx", tz=tz
+        )
+        result = idx.delete(-1)
+        tm.assert_index_equal(result, expected)
+        assert result.name == expected.name
+        assert result.freqstr == "h"
+        assert result.tz == expected.tz
+
+    def test_delete_slice(self, unit):
+        idx = date_range(
+            start="2000-01-01", periods=10, freq="D", name="idx", unit=unit
+        )
+
+        # preserve freq
+        expected_0_2 = date_range(
+            start="2000-01-04", periods=7, freq="D", name="idx", unit=unit
+        )
+        expected_7_9 = date_range(
+            start="2000-01-01", periods=7, freq="D", name="idx", unit=unit
+        )
+
+        # reset freq to None
+        expected_3_5 = DatetimeIndex(
+            [
+                "2000-01-01",
+                "2000-01-02",
+                "2000-01-03",
+                "2000-01-07",
+                "2000-01-08",
+                "2000-01-09",
+                "2000-01-10",
+            ],
+            freq=None,
+            name="idx",
+        ).as_unit(unit)
+
+        cases = {
+            (0, 1, 2): expected_0_2,
+            (7, 8, 9): expected_7_9,
+            (3, 4, 5): expected_3_5,
+        }
+        for n, expected in cases.items():
+            result = idx.delete(n)
+            tm.assert_index_equal(result, expected)
+            assert result.name == expected.name
+            assert result.freq == expected.freq
+
+            result = idx.delete(slice(n[0], n[-1] + 1))
+            tm.assert_index_equal(result, expected)
+            assert result.name == expected.name
+            assert result.freq == expected.freq
+
+    # TODO: belongs in Series.drop tests?
+    @pytest.mark.parametrize("tz", [None, "Asia/Tokyo", "US/Pacific"])
+    def test_delete_slice2(self, tz, unit):
+        dti = date_range(
+            "2000-01-01 09:00", periods=10, freq="h", name="idx", tz=tz, unit=unit
+        )
+        ts = Series(
+            1,
+            index=dti,
+        )
+        # preserve freq
+        result = ts.drop(ts.index[:5]).index
+        expected = dti[5:]
+        tm.assert_index_equal(result, expected)
+        assert result.name == expected.name
+        assert result.freq == expected.freq
+        assert result.tz == expected.tz
+
+        # reset freq to None
+        result = ts.drop(ts.index[[1, 3, 5, 7, 9]]).index
+        expected = dti[::2]._with_freq(None)
+        tm.assert_index_equal(result, expected)
+        assert result.name == expected.name
+        assert result.freq == expected.freq
+        assert result.tz == expected.tz

venv/lib/python3.10/site-packages/pandas/tests/indexes/datetimes/methods/test_factorize.py

@@ -0,0 +1,125 @@
+import numpy as np
+import pytest
+
+from pandas import (
+    DatetimeIndex,
+    Index,
+    date_range,
+    factorize,
+)
+import pandas._testing as tm
+
+
+class TestDatetimeIndexFactorize:
+    def test_factorize(self):
+        idx1 = DatetimeIndex(
+            ["2014-01", "2014-01", "2014-02", "2014-02", "2014-03", "2014-03"]
+        )
+
+        exp_arr = np.array([0, 0, 1, 1, 2, 2], dtype=np.intp)
+        exp_idx = DatetimeIndex(["2014-01", "2014-02", "2014-03"])
+
+        arr, idx = idx1.factorize()
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, exp_idx)
+        assert idx.freq == exp_idx.freq
+
+        arr, idx = idx1.factorize(sort=True)
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, exp_idx)
+        assert idx.freq == exp_idx.freq
+
+        # tz must be preserved
+        idx1 = idx1.tz_localize("Asia/Tokyo")
+        exp_idx = exp_idx.tz_localize("Asia/Tokyo")
+
+        arr, idx = idx1.factorize()
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, exp_idx)
+        assert idx.freq == exp_idx.freq
+
+        idx2 = DatetimeIndex(
+            ["2014-03", "2014-03", "2014-02", "2014-01", "2014-03", "2014-01"]
+        )
+
+        exp_arr = np.array([2, 2, 1, 0, 2, 0], dtype=np.intp)
+        exp_idx = DatetimeIndex(["2014-01", "2014-02", "2014-03"])
+        arr, idx = idx2.factorize(sort=True)
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, exp_idx)
+        assert idx.freq == exp_idx.freq
+
+        exp_arr = np.array([0, 0, 1, 2, 0, 2], dtype=np.intp)
+        exp_idx = DatetimeIndex(["2014-03", "2014-02", "2014-01"])
+        arr, idx = idx2.factorize()
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, exp_idx)
+        assert idx.freq == exp_idx.freq
+
+    def test_factorize_preserves_freq(self):
+        # GH#38120 freq should be preserved
+        idx3 = date_range("2000-01", periods=4, freq="ME", tz="Asia/Tokyo")
+        exp_arr = np.array([0, 1, 2, 3], dtype=np.intp)
+
+        arr, idx = idx3.factorize()
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, idx3)
+        assert idx.freq == idx3.freq
+
+        arr, idx = factorize(idx3)
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, idx3)
+        assert idx.freq == idx3.freq
+
+    def test_factorize_tz(self, tz_naive_fixture, index_or_series):
+        tz = tz_naive_fixture
+        # GH#13750
+        base = date_range("2016-11-05", freq="h", periods=100, tz=tz)
+        idx = base.repeat(5)
+
+        exp_arr = np.arange(100, dtype=np.intp).repeat(5)
+
+        obj = index_or_series(idx)
+
+        arr, res = obj.factorize()
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        expected = base._with_freq(None)
+        tm.assert_index_equal(res, expected)
+        assert res.freq == expected.freq
+
+    def test_factorize_dst(self, index_or_series):
+        # GH#13750
+        idx = date_range("2016-11-06", freq="h", periods=12, tz="US/Eastern")
+        obj = index_or_series(idx)
+
+        arr, res = obj.factorize()
+        tm.assert_numpy_array_equal(arr, np.arange(12, dtype=np.intp))
+        tm.assert_index_equal(res, idx)
+        if index_or_series is Index:
+            assert res.freq == idx.freq
+
+        idx = date_range("2016-06-13", freq="h", periods=12, tz="US/Eastern")
+        obj = index_or_series(idx)
+
+        arr, res = obj.factorize()
+        tm.assert_numpy_array_equal(arr, np.arange(12, dtype=np.intp))
+        tm.assert_index_equal(res, idx)
+        if index_or_series is Index:
+            assert res.freq == idx.freq
+
+    @pytest.mark.parametrize("sort", [True, False])
+    def test_factorize_no_freq_non_nano(self, tz_naive_fixture, sort):
+        # GH#51978 case that does not go through the fastpath based on
+        #  non-None freq
+        tz = tz_naive_fixture
+        idx = date_range("2016-11-06", freq="h", periods=5, tz=tz)[[0, 4, 1, 3, 2]]
+        exp_codes, exp_uniques = idx.factorize(sort=sort)
+
+        res_codes, res_uniques = idx.as_unit("s").factorize(sort=sort)
+
+        tm.assert_numpy_array_equal(res_codes, exp_codes)
+        tm.assert_index_equal(res_uniques, exp_uniques.as_unit("s"))
+
+        res_codes, res_uniques = idx.as_unit("s").to_series().factorize(sort=sort)
+        tm.assert_numpy_array_equal(res_codes, exp_codes)
+        tm.assert_index_equal(res_uniques, exp_uniques.as_unit("s"))

venv/lib/python3.10/site-packages/pandas/tests/indexes/datetimes/methods/test_fillna.py

@@ -0,0 +1,62 @@
+import pytest
+
+import pandas as pd
+import pandas._testing as tm
+
+
+class TestDatetimeIndexFillNA:
+    @pytest.mark.parametrize("tz", ["US/Eastern", "Asia/Tokyo"])
+    def test_fillna_datetime64(self, tz):
+        # GH 11343
+        idx = pd.DatetimeIndex(["2011-01-01 09:00", pd.NaT, "2011-01-01 11:00"])
+
+        exp = pd.DatetimeIndex(
+            ["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"]
+        )
+        tm.assert_index_equal(idx.fillna(pd.Timestamp("2011-01-01 10:00")), exp)
+
+        # tz mismatch
+        exp = pd.Index(
+            [
+                pd.Timestamp("2011-01-01 09:00"),
+                pd.Timestamp("2011-01-01 10:00", tz=tz),
+                pd.Timestamp("2011-01-01 11:00"),
+            ],
+            dtype=object,
+        )
+        tm.assert_index_equal(idx.fillna(pd.Timestamp("2011-01-01 10:00", tz=tz)), exp)
+
+        # object
+        exp = pd.Index(
+            [pd.Timestamp("2011-01-01 09:00"), "x", pd.Timestamp("2011-01-01 11:00")],
+            dtype=object,
+        )
+        tm.assert_index_equal(idx.fillna("x"), exp)
+
+        idx = pd.DatetimeIndex(["2011-01-01 09:00", pd.NaT, "2011-01-01 11:00"], tz=tz)
+
+        exp = pd.DatetimeIndex(
+            ["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"], tz=tz
+        )
+        tm.assert_index_equal(idx.fillna(pd.Timestamp("2011-01-01 10:00", tz=tz)), exp)
+
+        exp = pd.Index(
+            [
+                pd.Timestamp("2011-01-01 09:00", tz=tz),
+                pd.Timestamp("2011-01-01 10:00"),
+                pd.Timestamp("2011-01-01 11:00", tz=tz),
+            ],
+            dtype=object,
+        )
+        tm.assert_index_equal(idx.fillna(pd.Timestamp("2011-01-01 10:00")), exp)
+
+        # object
+        exp = pd.Index(
+            [
+                pd.Timestamp("2011-01-01 09:00", tz=tz),
+                "x",
+                pd.Timestamp("2011-01-01 11:00", tz=tz),
+            ],
+            dtype=object,
+        )
+        tm.assert_index_equal(idx.fillna("x"), exp)

venv/lib/python3.10/site-packages/pandas/tests/indexes/datetimes/methods/test_insert.py

@@ -0,0 +1,265 @@
+from datetime import datetime
+
+import numpy as np
+import pytest
+import pytz
+
+from pandas import (
+    NA,
+    DatetimeIndex,
+    Index,
+    NaT,
+    Timestamp,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestInsert:
+    @pytest.mark.parametrize("null", [None, np.nan, np.datetime64("NaT"), NaT, NA])
+    @pytest.mark.parametrize("tz", [None, "UTC", "US/Eastern"])
+    def test_insert_nat(self, tz, null):
+        # GH#16537, GH#18295 (test missing)
+
+        idx = DatetimeIndex(["2017-01-01"], tz=tz)
+        expected = DatetimeIndex(["NaT", "2017-01-01"], tz=tz)
+        if tz is not None and isinstance(null, np.datetime64):
+            expected = Index([null, idx[0]], dtype=object)
+
+        res = idx.insert(0, null)
+        tm.assert_index_equal(res, expected)
+
+    @pytest.mark.parametrize("tz", [None, "UTC", "US/Eastern"])
+    def test_insert_invalid_na(self, tz):
+        idx = DatetimeIndex(["2017-01-01"], tz=tz)
+
+        item = np.timedelta64("NaT")
+        result = idx.insert(0, item)
+        expected = Index([item] + list(idx), dtype=object)
+        tm.assert_index_equal(result, expected)
+
+    def test_insert_empty_preserves_freq(self, tz_naive_fixture):
+        # GH#33573
+        tz = tz_naive_fixture
+        dti = DatetimeIndex([], tz=tz, freq="D")
+        item = Timestamp("2017-04-05").tz_localize(tz)
+
+        result = dti.insert(0, item)
+        assert result.freq == dti.freq
+
+        # But not when we insert an item that doesn't conform to freq
+        dti = DatetimeIndex([], tz=tz, freq="W-THU")
+        result = dti.insert(0, item)
+        assert result.freq is None
+
+    def test_insert(self, unit):
+        idx = DatetimeIndex(
+            ["2000-01-04", "2000-01-01", "2000-01-02"], name="idx"
+        ).as_unit(unit)
+
+        result = idx.insert(2, datetime(2000, 1, 5))
+        exp = DatetimeIndex(
+            ["2000-01-04", "2000-01-01", "2000-01-05", "2000-01-02"], name="idx"
+        ).as_unit(unit)
+        tm.assert_index_equal(result, exp)
+
+        # insertion of non-datetime should coerce to object index
+        result = idx.insert(1, "inserted")
+        expected = Index(
+            [
+                datetime(2000, 1, 4),
+                "inserted",
+                datetime(2000, 1, 1),
+                datetime(2000, 1, 2),
+            ],
+            name="idx",
+        )
+        assert not isinstance(result, DatetimeIndex)
+        tm.assert_index_equal(result, expected)
+        assert result.name == expected.name
+
+    def test_insert2(self, unit):
+        idx = date_range("1/1/2000", periods=3, freq="ME", name="idx", unit=unit)
+
+        # preserve freq
+        expected_0 = DatetimeIndex(
+            ["1999-12-31", "2000-01-31", "2000-02-29", "2000-03-31"],
+            name="idx",
+            freq="ME",
+        ).as_unit(unit)
+        expected_3 = DatetimeIndex(
+            ["2000-01-31", "2000-02-29", "2000-03-31", "2000-04-30"],
+            name="idx",
+            freq="ME",
+        ).as_unit(unit)
+
+        # reset freq to None
+        expected_1_nofreq = DatetimeIndex(
+            ["2000-01-31", "2000-01-31", "2000-02-29", "2000-03-31"],
+            name="idx",
+            freq=None,
+        ).as_unit(unit)
+        expected_3_nofreq = DatetimeIndex(
+            ["2000-01-31", "2000-02-29", "2000-03-31", "2000-01-02"],
+            name="idx",
+            freq=None,
+        ).as_unit(unit)
+
+        cases = [
+            (0, datetime(1999, 12, 31), expected_0),
+            (-3, datetime(1999, 12, 31), expected_0),
+            (3, datetime(2000, 4, 30), expected_3),
+            (1, datetime(2000, 1, 31), expected_1_nofreq),
+            (3, datetime(2000, 1, 2), expected_3_nofreq),
+        ]
+
+        for n, d, expected in cases:
+            result = idx.insert(n, d)
+            tm.assert_index_equal(result, expected)
+            assert result.name == expected.name
+            assert result.freq == expected.freq
+
+    def test_insert3(self, unit):
+        idx = date_range("1/1/2000", periods=3, freq="ME", name="idx", unit=unit)
+
+        # reset freq to None
+        result = idx.insert(3, datetime(2000, 1, 2))
+        expected = DatetimeIndex(
+            ["2000-01-31", "2000-02-29", "2000-03-31", "2000-01-02"],
+            name="idx",
+            freq=None,
+        ).as_unit(unit)
+        tm.assert_index_equal(result, expected)
+        assert result.name == expected.name
+        assert result.freq is None
+
+    def test_insert4(self, unit):
+        for tz in ["US/Pacific", "Asia/Singapore"]:
+            idx = date_range(
+                "1/1/2000 09:00", periods=6, freq="h", tz=tz, name="idx", unit=unit
+            )
+            # preserve freq
+            expected = date_range(
+                "1/1/2000 09:00", periods=7, freq="h", tz=tz, name="idx", unit=unit
+            )
+            for d in [
+                Timestamp("2000-01-01 15:00", tz=tz),
+                pytz.timezone(tz).localize(datetime(2000, 1, 1, 15)),
+            ]:
+                result = idx.insert(6, d)
+                tm.assert_index_equal(result, expected)
+                assert result.name == expected.name
+                assert result.freq == expected.freq
+                assert result.tz == expected.tz
+
+            expected = DatetimeIndex(
+                [
+                    "2000-01-01 09:00",
+                    "2000-01-01 10:00",
+                    "2000-01-01 11:00",
+                    "2000-01-01 12:00",
+                    "2000-01-01 13:00",
+                    "2000-01-01 14:00",
+                    "2000-01-01 10:00",
+                ],
+                name="idx",
+                tz=tz,
+                freq=None,
+            ).as_unit(unit)
+            # reset freq to None
+            for d in [
+                Timestamp("2000-01-01 10:00", tz=tz),
+                pytz.timezone(tz).localize(datetime(2000, 1, 1, 10)),
+            ]:
+                result = idx.insert(6, d)
+                tm.assert_index_equal(result, expected)
+                assert result.name == expected.name
+                assert result.tz == expected.tz
+                assert result.freq is None
+
+    # TODO: also changes DataFrame.__setitem__ with expansion
+    def test_insert_mismatched_tzawareness(self):
+        # see GH#7299
+        idx = date_range("1/1/2000", periods=3, freq="D", tz="Asia/Tokyo", name="idx")
+
+        # mismatched tz-awareness
+        item = Timestamp("2000-01-04")
+        result = idx.insert(3, item)
+        expected = Index(
+            list(idx[:3]) + [item] + list(idx[3:]), dtype=object, name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+
+        # mismatched tz-awareness
+        item = datetime(2000, 1, 4)
+        result = idx.insert(3, item)
+        expected = Index(
+            list(idx[:3]) + [item] + list(idx[3:]), dtype=object, name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+
+    # TODO: also changes DataFrame.__setitem__ with expansion
+    def test_insert_mismatched_tz(self):
+        # see GH#7299
+        # pre-2.0 with mismatched tzs we would cast to object
+        idx = date_range("1/1/2000", periods=3, freq="D", tz="Asia/Tokyo", name="idx")
+
+        # mismatched tz -> cast to object (could reasonably cast to same tz or UTC)
+        item = Timestamp("2000-01-04", tz="US/Eastern")
+        result = idx.insert(3, item)
+        expected = Index(
+            list(idx[:3]) + [item.tz_convert(idx.tz)] + list(idx[3:]),
+            name="idx",
+        )
+        assert expected.dtype == idx.dtype
+        tm.assert_index_equal(result, expected)
+
+        item = datetime(2000, 1, 4, tzinfo=pytz.timezone("US/Eastern"))
+        result = idx.insert(3, item)
+        expected = Index(
+            list(idx[:3]) + [item.astimezone(idx.tzinfo)] + list(idx[3:]),
+            name="idx",
+        )
+        assert expected.dtype == idx.dtype
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "item", [0, np.int64(0), np.float64(0), np.array(0), np.timedelta64(456)]
+    )
+    def test_insert_mismatched_types_raises(self, tz_aware_fixture, item):
+        # GH#33703 dont cast these to dt64
+        tz = tz_aware_fixture
+        dti = date_range("2019-11-04", periods=9, freq="-1D", name=9, tz=tz)
+
+        result = dti.insert(1, item)
+
+        if isinstance(item, np.ndarray):
+            assert item.item() == 0
+            expected = Index([dti[0], 0] + list(dti[1:]), dtype=object, name=9)
+        else:
+            expected = Index([dti[0], item] + list(dti[1:]), dtype=object, name=9)
+
+        tm.assert_index_equal(result, expected)
+
+    def test_insert_castable_str(self, tz_aware_fixture):
+        # GH#33703
+        tz = tz_aware_fixture
+        dti = date_range("2019-11-04", periods=3, freq="-1D", name=9, tz=tz)
+
+        value = "2019-11-05"
+        result = dti.insert(0, value)
+
+        ts = Timestamp(value).tz_localize(tz)
+        expected = DatetimeIndex([ts] + list(dti), dtype=dti.dtype, name=9)
+        tm.assert_index_equal(result, expected)
+
+    def test_insert_non_castable_str(self, tz_aware_fixture):
+        # GH#33703
+        tz = tz_aware_fixture
+        dti = date_range("2019-11-04", periods=3, freq="-1D", name=9, tz=tz)
+
+        value = "foo"
+        result = dti.insert(0, value)
+
+        expected = Index(["foo"] + list(dti), dtype=object, name=9)
+        tm.assert_index_equal(result, expected)

venv/lib/python3.10/site-packages/pandas/tests/indexes/datetimes/methods/test_isocalendar.py

@@ -0,0 +1,28 @@
+from pandas import (
+    DataFrame,
+    DatetimeIndex,
+    date_range,
+)
+import pandas._testing as tm
+
+
+def test_isocalendar_returns_correct_values_close_to_new_year_with_tz():
+    # GH#6538: Check that DatetimeIndex and its TimeStamp elements
+    # return the same weekofyear accessor close to new year w/ tz
+    dates = ["2013/12/29", "2013/12/30", "2013/12/31"]
+    dates = DatetimeIndex(dates, tz="Europe/Brussels")
+    result = dates.isocalendar()
+    expected_data_frame = DataFrame(
+        [[2013, 52, 7], [2014, 1, 1], [2014, 1, 2]],
+        columns=["year", "week", "day"],
+        index=dates,
+        dtype="UInt32",
+    )
+    tm.assert_frame_equal(result, expected_data_frame)
+
+
+def test_dti_timestamp_isocalendar_fields():
+    idx = date_range("2020-01-01", periods=10)
+    expected = tuple(idx.isocalendar().iloc[-1].to_list())
+    result = idx[-1].isocalendar()
+    assert result == expected

venv/lib/python3.10/site-packages/pandas/tests/indexes/datetimes/methods/test_map.py

@@ -0,0 +1,47 @@
+import pytest
+
+from pandas import (
+    DatetimeIndex,
+    Index,
+    MultiIndex,
+    Period,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestMap:
+    def test_map(self):
+        rng = date_range("1/1/2000", periods=10)
+
+        f = lambda x: x.strftime("%Y%m%d")
+        result = rng.map(f)
+        exp = Index([f(x) for x in rng])
+        tm.assert_index_equal(result, exp)
+
+    def test_map_fallthrough(self, capsys):
+        # GH#22067, check we don't get warnings about silently ignored errors
+        dti = date_range("2017-01-01", "2018-01-01", freq="B")
+
+        dti.map(lambda x: Period(year=x.year, month=x.month, freq="M"))
+
+        captured = capsys.readouterr()
+        assert captured.err == ""
+
+    def test_map_bug_1677(self):
+        index = DatetimeIndex(["2012-04-25 09:30:00.393000"])
+        f = index.asof
+
+        result = index.map(f)
+        expected = Index([f(index[0])])
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize("name", [None, "name"])
+    def test_index_map(self, name):
+        # see GH#20990
+        count = 6
+        index = date_range("2018-01-01", periods=count, freq="ME", name=name).map(
+            lambda x: (x.year, x.month)
+        )
+        exp_index = MultiIndex.from_product(((2018,), range(1, 7)), names=[name, name])
+        tm.assert_index_equal(index, exp_index)

venv/lib/python3.10/site-packages/pandas/tests/indexes/datetimes/methods/test_normalize.py

@@ -0,0 +1,95 @@
+from dateutil.tz import tzlocal
+import numpy as np
+import pytest
+
+import pandas.util._test_decorators as td
+
+from pandas import (
+    DatetimeIndex,
+    NaT,
+    Timestamp,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestNormalize:
+    def test_normalize(self):
+        rng = date_range("1/1/2000 9:30", periods=10, freq="D")
+
+        result = rng.normalize()
+        expected = date_range("1/1/2000", periods=10, freq="D")
+        tm.assert_index_equal(result, expected)
+
+        arr_ns = np.array([1380585623454345752, 1380585612343234312]).astype(
+            "datetime64[ns]"
+        )
+        rng_ns = DatetimeIndex(arr_ns)
+        rng_ns_normalized = rng_ns.normalize()
+
+        arr_ns = np.array([1380585600000000000, 1380585600000000000]).astype(
+            "datetime64[ns]"
+        )
+        expected = DatetimeIndex(arr_ns)
+        tm.assert_index_equal(rng_ns_normalized, expected)
+
+        assert result.is_normalized
+        assert not rng.is_normalized
+
+    def test_normalize_nat(self):
+        dti = DatetimeIndex([NaT, Timestamp("2018-01-01 01:00:00")])
+        result = dti.normalize()
+        expected = DatetimeIndex([NaT, Timestamp("2018-01-01")])
+        tm.assert_index_equal(result, expected)
+
+    def test_normalize_tz(self):
+        rng = date_range("1/1/2000 9:30", periods=10, freq="D", tz="US/Eastern")
+
+        result = rng.normalize()  # does not preserve freq
+        expected = date_range("1/1/2000", periods=10, freq="D", tz="US/Eastern")
+        tm.assert_index_equal(result, expected._with_freq(None))
+
+        assert result.is_normalized
+        assert not rng.is_normalized
+
+        rng = date_range("1/1/2000 9:30", periods=10, freq="D", tz="UTC")
+
+        result = rng.normalize()
+        expected = date_range("1/1/2000", periods=10, freq="D", tz="UTC")
+        tm.assert_index_equal(result, expected)
+
+        assert result.is_normalized
+        assert not rng.is_normalized
+
+        rng = date_range("1/1/2000 9:30", periods=10, freq="D", tz=tzlocal())
+        result = rng.normalize()  # does not preserve freq
+        expected = date_range("1/1/2000", periods=10, freq="D", tz=tzlocal())
+        tm.assert_index_equal(result, expected._with_freq(None))
+
+        assert result.is_normalized
+        assert not rng.is_normalized
+
+    @td.skip_if_windows
+    @pytest.mark.parametrize(
+        "timezone",
+        [
+            "US/Pacific",
+            "US/Eastern",
+            "UTC",
+            "Asia/Kolkata",
+            "Asia/Shanghai",
+            "Australia/Canberra",
+        ],
+    )
+    def test_normalize_tz_local(self, timezone):
+        # GH#13459
+        with tm.set_timezone(timezone):
+            rng = date_range("1/1/2000 9:30", periods=10, freq="D", tz=tzlocal())
+
+            result = rng.normalize()
+            expected = date_range("1/1/2000", periods=10, freq="D", tz=tzlocal())
+            expected = expected._with_freq(None)
+            tm.assert_index_equal(result, expected)
+
+            assert result.is_normalized
+            assert not rng.is_normalized

venv/lib/python3.10/site-packages/pandas/tests/indexes/datetimes/methods/test_repeat.py

@@ -0,0 +1,83 @@
+import numpy as np
+import pytest
+
+from pandas import (
+    DatetimeIndex,
+    Timestamp,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestRepeat:
+    def test_repeat_range(self, tz_naive_fixture):
+        rng = date_range("1/1/2000", "1/1/2001")
+
+        result = rng.repeat(5)
+        assert result.freq is None
+        assert len(result) == 5 * len(rng)
+
+    def test_repeat_range2(self, tz_naive_fixture, unit):
+        tz = tz_naive_fixture
+        index = date_range("2001-01-01", periods=2, freq="D", tz=tz, unit=unit)
+        exp = DatetimeIndex(
+            ["2001-01-01", "2001-01-01", "2001-01-02", "2001-01-02"], tz=tz
+        ).as_unit(unit)
+        for res in [index.repeat(2), np.repeat(index, 2)]:
+            tm.assert_index_equal(res, exp)
+            assert res.freq is None
+
+    def test_repeat_range3(self, tz_naive_fixture, unit):
+        tz = tz_naive_fixture
+        index = date_range("2001-01-01", periods=2, freq="2D", tz=tz, unit=unit)
+        exp = DatetimeIndex(
+            ["2001-01-01", "2001-01-01", "2001-01-03", "2001-01-03"], tz=tz
+        ).as_unit(unit)
+        for res in [index.repeat(2), np.repeat(index, 2)]:
+            tm.assert_index_equal(res, exp)
+            assert res.freq is None
+
+    def test_repeat_range4(self, tz_naive_fixture, unit):
+        tz = tz_naive_fixture
+        index = DatetimeIndex(["2001-01-01", "NaT", "2003-01-01"], tz=tz).as_unit(unit)
+        exp = DatetimeIndex(
+            [
+                "2001-01-01",
+                "2001-01-01",
+                "2001-01-01",
+                "NaT",
+                "NaT",
+                "NaT",
+                "2003-01-01",
+                "2003-01-01",
+                "2003-01-01",
+            ],
+            tz=tz,
+        ).as_unit(unit)
+        for res in [index.repeat(3), np.repeat(index, 3)]:
+            tm.assert_index_equal(res, exp)
+            assert res.freq is None
+
+    def test_repeat(self, tz_naive_fixture, unit):
+        tz = tz_naive_fixture
+        reps = 2
+        msg = "the 'axis' parameter is not supported"
+
+        rng = date_range(start="2016-01-01", periods=2, freq="30Min", tz=tz, unit=unit)
+
+        expected_rng = DatetimeIndex(
+            [
+                Timestamp("2016-01-01 00:00:00", tz=tz),
+                Timestamp("2016-01-01 00:00:00", tz=tz),
+                Timestamp("2016-01-01 00:30:00", tz=tz),
+                Timestamp("2016-01-01 00:30:00", tz=tz),
+            ]
+        ).as_unit(unit)
+
+        res = rng.repeat(reps)
+        tm.assert_index_equal(res, expected_rng)
+        assert res.freq is None
+
+        tm.assert_index_equal(np.repeat(rng, reps), expected_rng)
+        with pytest.raises(ValueError, match=msg):
+            np.repeat(rng, reps, axis=1)