common --repo_env=ML_WHEEL_BUILD_DATE=""
common --repo_env=ML_WHEEL_VERSION_SUFFIX=""

# For projects which use TensorFlow as part of a Bazel build process, putting
# nothing in a bazelrc will default to a monolithic build. The following line
# opts in to modular op registration support by default.
common --define framework_shared_object=true
common --define tsl_protobuf_header_only=true

common --define=allow_oversize_protos=true

```sh
mc admin config set myminio/ notify_redis:1 address="127.0.0.1:6379" format="namespace" key="bucketevents" password="yoursecret" queue_dir="" queue_limit="0"
```

	}
	data = data[len(line):]
	line, isPrefix, err = l.ReadLine()
	if isPrefix || !bytes.Equal(line, data[:minReadBufferSize/2]) || err != nil {
		t.Errorf("bad result for third line: got %q want %q %v", line, data[:minReadBufferSize/2], err)
	}
	line, isPrefix, err = l.ReadLine()
	if isPrefix || err == nil {
		t.Errorf("expected no more lines: %x %s", line, err)
	}
}

                }
            }

            // effective line, with indent and reset if end is colored
            line = indent + line + ("".equals(nextColor) ? "" : ANSI_RESET);

            if ((i == lines.length - 1) && (showErrors || (summary.getException() instanceof InternalErrorException))) {
                slf4jLogger.error(line, summary.getException());
            } else {

            "axisCenteredZero": false,
            "axisColorMode": "text",
            "axisLabel": "",
            "axisPlacement": "auto",
            "barAlignment": 0,
            "drawStyle": "line",
            "fillOpacity": 10,
            "gradientMode": "none",
            "hideFrom": {
              "legend": false,
              "tooltip": false,
              "viz": false
            },

            "axisCenteredZero": false,
            "axisColorMode": "text",
            "axisLabel": "",
            "axisPlacement": "auto",
            "barAlignment": 0,
            "drawStyle": "line",
            "fillOpacity": 10,
            "gradientMode": "none",
            "hideFrom": {
              "legend": false,
              "tooltip": false,
              "viz": false
            },

        "//tensorflow/lite/c:common",
        "//tensorflow/lite/core/api",
        "//tensorflow/lite/delegates/flex:delegate",
        "//tensorflow/lite/kernels/internal:compatibility",
        "//tensorflow/lite/kernels:builtin_ops",
        "//tensorflow/lite/kernels:reference_ops",
        "//tensorflow/compiler/mlir/lite/schema:schema_fbs",
        "//tensorflow/lite/toco/logging:conversion_log_util",

            "axisCenteredZero": false,
            "axisColorMode": "text",
            "axisLabel": "",
            "axisPlacement": "auto",
            "barAlignment": 0,
            "drawStyle": "line",
            "fillOpacity": 10,
            "gradientMode": "none",
            "hideFrom": {
              "legend": false,
              "tooltip": false,
              "viz": false
            },

		t.Fatalf("got error: %v", err)
	}

	if len(users) != 4 {
		t.Errorf("Four users should be found, instead found %d", len(users))
	}

	DB.Select("*").Where("name LIKE ?", "subquery%").Where("age >= (?)", DB.
		Select("AVG(age)").Table("users").Where("name LIKE ?", "subquery%")).Find(&users)

    Tensor output;
    ASSERT_EQ(absl::OkStatus(), TF_TensorToTensor(dst, &output)) << line;
    ASSERT_EQ(src.NumElements(), output.NumElements()) << line;
    for (int64_t i = 0; i < src.NumElements(); ++i) {
      ASSERT_EQ(data[i], output.flat<tstring>()(i)) << line;
    }

    TF_DeleteTensor(dst);
  }
}

TEST(CAPI, TensorEncodeDecodeStrings) {